{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('tcp', 270), ('udp', 220), ('147.32.84.229', 186), ('13363', 88), ('147.32.80.9', 73), ('53', 73), ('80', 70), ('147.32.84.59', 59), ('443', 43), ('147.32.84.118', 41), ('6881', 39), ('147.32.85.25', 39), ('140.115.25.74', 30), ('147.32.84.138', 29), ('147.32.86.165', 25), ('173.242.220.227', 17), ('147.32.84.111', 17), ('188.121.222.1', 12), ('147.32.84.2', 11), ('147.32.3.51', 10), ('10010', 10), ('43087', 8), ('122.174.15.39', 7), ('12114', 7), ('147.32.87.22', 6), ('77.78.99.22', 6), ('147.32.86.24', 6), ('91.207.59.162', 6), ('203.23.120.136', 5), ('147.32.84.46', 4), ('147.32.86.166', 4), ('147.32.85.56', 4), ('147.32.86.223', 4), ('74.125.232.213', 4), ('74.125.232.220', 4), ('88.212.37.169', 3), ('94.44.60.103', 3), ('188.112.125.201', 3), ('212.201.86.130', 3), ('92.40.253.219', 3), ('147.32.80.13', 3), ('147.32.86.110', 3), ('8080', 3), ('213.155.227.215', 3), ('74.125.232.215', 3), ('161', 3), ('123', 3), ('147.32.85.18', 3), ('2.159.127.100', 2), ('85.132.162.9', 2), ('147.32.85.124', 2), ('77.78.99.21', 2), ('147.32.96.45', 2), ('147.32.84.165', 2), ('21', 2), ('89.223.179.146', 2), ('147.32.192.34', 2), ('993', 2), ('115.184.37.24', 2), ('31002', 2), ('151.41.188.39', 2), ('82.209.194.12', 2), ('194.108.204.22', 2), ('147.32.86.53', 2), ('44076', 2), ('147.32.87.220', 2), ('81.81.67.46', 2), ('62.44.1.24', 2), ('147.32.84.94', 2), ('147.32.84.164', 2), ('89.221.217.12', 2), ('1935', 2), ('22', 2), ('77.246.52.166', 2), ('194.108.204.19', 2), ('94.100.187.194', 2), ('74.125.232.216', 2), ('147.32.85.8', 2), ('109.149.84.86', 2), ('147.32.86.147', 2), ('147.32.86.111', 2), ('147.32.86.20', 2), ('88.86.102.50', 2), ('5222', 2), ('147.32.87.254', 2), ('91.123.225.57', 2), ('93.45.239.29', 1), ('62.240.166.118', 1), ('147.32.86.148', 1), ('66.235.132.232', 1), ('213.233.154.219', 1), ('95.210.161.212', 1), ('2.159.25.101', 1), ('213.233.154.226', 1), ('95.153.189.22', 1), ('77.75.73.9', 1), ('178.255.217.104', 1), ('193.6.144.62', 1), ('31.64.164.71', 1), ('66.29.191.18', 1), ('99.141.169.24', 1), ('4793', 1), ('196.201.19.50', 1), ('74.125.232.219', 1), ('195.113.232.82', 1), ('212.24.150.110', 1), ('25443', 1), ('82.39.2.249', 1), ('80.78.79.156', 1), ('49621', 1), ('82.73.244.56', 1), ('1153', 1), ('188.95.61.42', 1), ('48190', 1), ('192.221.106.126', 1), ('2774', 1), ('212.111.2.151', 1), ('147.32.86.135', 1), ('3978', 1), ('95.172.94.54', 1), ('114.78.14.160', 1), ('147.32.85.88', 1), ('56949', 1), ('195.250.146.100', 1), ('8000', 1), ('115.108.130.214', 1), ('122.176.204.167', 1), ('16041', 1), ('147.32.82.101', 1), ('147.32.86.88', 1), ('3389', 1), ('147.32.85.74', 1), ('147.32.203.229', 1), ('2971', 1), ('193.87.80.3', 1), ('51019', 1), ('95.227.158.77', 1), ('60330', 1), ('84.222.204.28', 1), ('67.218.100.83', 1), ('24.4.101.240', 1), ('147.213.68.141', 1), ('1040', 1), ('147.32.89.184', 1), ('58898', 1), ('86.161.84.198', 1), ('151.45.215.195', 1), ('1059', 1), ('59277', 1), ('192.134.164.161', 1), ('192.166.145.21', 1), ('74.125.232.214', 1), ('48102', 1), ('192.166.145.6', 1), ('49198', 1), ('85.237.224.48', 1), ('89.135.152.106', 1), ('1126', 1), ('211.101.37.103', 1), ('195.72.134.115', 1), ('195.130.82.45', 1), ('116.50.166.74', 1), ('46.5.184.57', 1), ('36165', 1), ('217.150.190.17', 1), ('74.125.108.208', 1), ('2768', 1), ('41.130.235.95', 1), ('212.239.26.199', 1), ('51572', 1), ('58.182.2.6', 1), ('147.32.87.30', 1), ('46.158.48.2', 1), ('178.200.203.145', 1), ('7300', 1), ('81.57.190.106', 1), ('6911', 1), ('77.127.196.107', 1), ('147.32.84.73', 1), ('113.161.71.62', 1), ('38217', 1), ('115.173.243.205', 1), ('194.161.219.176', 1), ('51003', 1), ('31.162.200.244', 1), ('174.98.117.98', 1), ('77.126.195.83', 1), ('23065', 1), ('85.207.55.78', 1), ('130.192.181.149', 1), ('68.51.197.191', 1), ('21348', 1), ('114.26.174.109', 1), ('31056', 1), ('77.85.143.253', 1), ('95.149.168.251', 1), ('81.20.48.51', 1), ('39836', 1), ('94.179.103.184', 1), ('84.12.54.36', 1), ('203.125.50.50', 1), ('2.32.222.83', 1), ('195.24.232.164', 1), ('34588', 1), ('196.44.240.61', 1), ('49.240.140.102', 1), ('80.239.149.26', 1), ('201.209.15.135', 1), ('94.126.186.67', 1), ('86.100.133.199', 1), ('58.8.226.198', 1), ('223.205.214.227', 1), ('98.244.73.136', 1), ('147.32.97.253', 1), ('147.32.84.8', 1), ('113.65.40.102', 1), ('195.250.146.6', 1), ('49340', 1), ('53538', 1), ('78.128.194.184', 1), ('147.32.84.68', 1), ('52948', 1), ('78.80.14.227', 1), ('147.32.84.3', 1), ('41343', 1), ('109.164.3.183', 1), ('85.70.149.37', 1), ('3360', 1), ('141.156.150.237', 1), ('82.199.111.22', 1), ('46.191.167.153', 1), ('195.239.66.250', 1), ('50973', 1), ('147.32.85.34', 1), ('35149', 1), ('67.160.121.194', 1), ('126.170.234.66', 1), ('95.52.90.246', 1), ('53185', 1), ('78.84.137.106', 1), ('30657', 1), ('116.255.12.184', 1), ('55584', 1), ('24.247.253.8', 1), ('34092', 1), ('83.11.238.15', 1), ('147.32.86.239', 1), ('62.24.66.210', 1), ('178.90.23.47', 1), ('147.32.85.89', 1), ('147.32.85.26', 1), ('209.85.148.147', 1), ('109.175.50.70', 1), ('1194', 1), ('117.194.42.208', 1), ('33482', 1), ('114.138.217.214', 1), ('9146', 1), ('178.253.242.3', 1), ('178.2.216.156', 1), ('147.32.84.21', 1), ('44146', 1), ('78.90.84.134', 1), ('147.230.32.193', 1), ('194.228.143.168', 1), ('16516', 1), ('90.183.39.86', 1), ('85.13.72.246', 1), ('147.32.87.2', 1), ('76.13.114.90', 1), ('81.90.173.232', 1), ('88.177.153.150', 1), ('23739', 1), ('114.45.250.190', 1), ('1942', 1), ('147.32.87.48', 1), ('147.32.86.252', 1), ('82.177.229.240', 1), ('41.241.93.111', 1), ('76.164.192.82', 1), ('147.32.86.117', 1), ('16476', 1), ('130.236.37.3', 1), ('57989', 1), ('90.183.38.8', 1), ('49463', 1), ('218.209.43.8', 1), ('87.244.151.27', 1), ('31518', 1), ('89.178.50.15', 1), ('1273', 1), ('94.179.93.205', 1), ('3605', 1), ('74.125.232.202', 1), ('94.74.233.93', 1), ('113.105.171.56', 1), ('147.32.86.66', 1), ('40565', 1), ('192.100.130.7', 1), ('212.235.185.142', 1), ('20992', 1), ('21835', 1), ('147.32.84.184', 1), ('199.59.149.200', 1), ('188.175.127.220', 1), ('203.99.179.112', 1), ('74.215.40.251', 1), ('159.148.227.125', 1), ('49230', 1), ('60.250.102.130', 1), ('94.198.111.82', 1), ('193.142.0.1', 1), ('193.165.4.137', 1), ('183.83.130.244', 1), ('85.117.224.50', 1), ('67.195.115.177', 1), ('147.32.87.27', 1), ('147.32.85.5', 1), ('52316', 1), ('83.228.35.75', 1), ('78.141.177.63', 1), ('194.129.65.79', 1), ('109.153.100.95', 1), ('84.217.37.3', 1), ('55840', 1), ('205.188.10.189', 1), ('95.32.5.235', 1), ('109.11.239.168', 1), ('201.79.47.179', 1), ('54239', 1), ('182.170.250.154', 1), ('55316', 1), ('79.50.93.42', 1), ('45974', 1), ('222.145.103.227', 1), ('69.238.171.67', 1), ('77.120.178.242', 1), ('15451', 1), ('124.102.16.132', 1), ('195.18.192.176', 1), ('118.165.82.114', 1), ('42796', 1), ('85.14.18.164', 1), ('32410', 1), ('192.168.1.99', 1), ('110.1.150.128', 1), ('188.138.84.239', 1), ('178.126.213.97', 1), ('62.118.200.4', 1), ('76.91.139.18', 1), ('5318', 1), ('91.148.14.80', 1), ('88.1.124.189', 1), ('188.244.37.212', 1), ('151.50.42.148', 1), ('90.178.130.71', 1), ('219.95.99.182', 1), ('81.145.244.43', 1), ('86.63.194.225', 1), ('129.6.15.28', 1), ('119.82.68.244', 1), ('3689', 1), ('64.228.86.17', 1), ('59156', 1), ('68.227.9.121', 1), ('38769', 1), ('94.155.203.122', 1), ('41688', 1), ('77.37.194.251', 1), ('10733', 1), ('118.233.160.13', 1), ('29930', 1), ('98.166.254.26', 1), ('16775', 1), ('78.141.181.221', 1), ('34049', 1), ('61.219.106.199', 1), ('22015', 1), ('79.180.232.121', 1), ('33791', 1), ('121.218.171.254', 1), ('59229', 1), ('119.194.132.184', 1), ('94.45.56.221', 1), ('14711', 1), ('88.160.241.60', 1), ('13631', 1), ('85.122.145.220', 1), ('63231', 1), ('24.218.41.238', 1), ('42643', 1), ('82.243.178.156', 1), ('24211', 1), ('96.20.140.58', 1), ('55397', 1), ('60.250.85.109', 1), ('37514', 1), ('114.40.141.216', 1), ('18082', 1), ('60.248.145.115', 1), ('8206', 1), ('68.144.201.22', 1), ('58975', 1), ('70.64.246.26', 1), ('16832', 1), ('84.229.5.224', 1), ('8824', 1), ('46.127.53.27', 1), ('44593', 1), ('92.247.216.178', 1), ('52613', 1), ('88.193.88.76', 1), ('58676', 1), ('84.38.184.4', 1), ('49341', 1), ('147.32.86.181', 1), ('147.32.3.12', 1), ('4628', 1), ('78.231.189.116', 1), ('63550', 1), ('91.207.59.161', 1), ('2641', 1), ('62.245.98.34', 1), ('14065', 1), ('82.135.148.158', 1), ('147.32.86.6', 1), ('208.46.117.171', 1), ('3478', 1), ('149.5.45.8', 1), ('43017', 1), ('84.42.148.179', 1), ('49653', 1), ('85.193.5.150', 1), ('195.110.40.7', 1), ('174.48.220.201', 1), ('178.4.36.49', 1), ('201.231.168.71', 1), ('147.229.74.152', 1), ('43117', 1), ('194.242.41.77', 1), ('84.112.212.191', 1), ('13723', 1), ('77.72.244.45', 1), ('26388', 1), ('213.226.244.55', 1), ('2739', 1), ('220.130.40.204', 1), ('12748', 1), ('122.116.188.88', 1), ('18510', 1), ('128.32.224.18', 1), ('37200', 1), ('76.27.46.107', 1), ('55557', 1), ('69.204.160.28', 1), ('23055', 1), ('87.0.21.115', 1), ('130.75.243.145', 1), ('3312', 1), ('205.188.8.254', 1), ('1071', 1), ('125.66.203.116', 1), ('4669', 1), ('2755', 1), ('2756', 1), ('122.174.115.150', 1), ('2164', 1), ('147.32.86.77', 1), ('68.37.66.192', 1), ('13873', 1), ('41.132.73.182', 1), ('23018', 1), ('94.127.76.194', 1), ('50188', 1), ('2762', 1), ('2760', 1), ('2759', 1), ('63.135.80.58', 1), ('66.150.244.242', 1), ('137.254.16.69', 1), ('147.32.85.103', 1), ('49311', 1), ('213.226.63.145', 1), ('46.10.96.224', 1), ('3412', 1), ('218.43.165.32', 1), ('192.84.221.33', 1), ('55000', 1), ('110.134.149.49', 1), ('40261', 1), ('147.32.85.60', 1), ('77.78.110.71', 1), ('113.234.168.192', 1), ('195.200.251.89', 1)]\n",
      "147.32.84.21:0\n",
      "2759:1\n",
      "203.125.50.50:2\n",
      "46.158.48.2:3\n",
      "74.125.232.214:4\n",
      "76.13.114.90:5\n",
      "51572:6\n",
      "86.161.84.198:7\n",
      "178.4.36.49:8\n",
      "52316:9\n",
      "58.8.226.198:10\n",
      "51019:11\n",
      "5318:12\n",
      "31518:13\n",
      "147.32.84.68:14\n",
      "69.204.160.28:15\n",
      "192.166.145.6:16\n",
      "13363:17\n",
      "67.160.121.194:18\n",
      "95.149.168.251:19\n",
      "94.198.111.82:20\n",
      "147.32.84.165:21\n",
      "95.227.158.77:22\n",
      "4793:23\n",
      "6911:24\n",
      "88.160.241.60:25\n",
      "203.99.179.112:26\n",
      "88.193.88.76:27\n",
      "8000:28\n",
      "129.6.15.28:29\n",
      "21:30\n",
      "211.101.37.103:31\n",
      "147.32.86.148:32\n",
      "201.79.47.179:33\n",
      "49621:34\n",
      "8080:35\n",
      "22:36\n",
      "194.228.143.168:37\n",
      "84.112.212.191:38\n",
      "58975:39\n",
      "49311:40\n",
      "147.32.203.229:41\n",
      "35149:42\n",
      "178.253.242.3:43\n",
      "40261:44\n",
      "85.13.72.246:45\n",
      "10733:46\n",
      "110.134.149.49:47\n",
      "88.177.153.150:48\n",
      "147.32.84.138:49\n",
      "15451:50\n",
      "3360:51\n",
      "38769:52\n",
      "125.66.203.116:53\n",
      "140.115.25.74:54\n",
      "92.40.253.219:55\n",
      "41688:56\n",
      "195.200.251.89:57\n",
      "10010:58\n",
      "188.112.125.201:59\n",
      "195.130.82.45:60\n",
      "14711:61\n",
      "147.32.86.165:62\n",
      "2641:63\n",
      "77.78.110.71:64\n",
      "119.82.68.244:65\n",
      "110.1.150.128:66\n",
      "147.32.85.74:67\n",
      "217.150.190.17:68\n",
      "94.127.76.194:69\n",
      "159.148.227.125:70\n",
      "74.125.232.215:71\n",
      "77.75.73.9:72\n",
      "147.32.86.88:73\n",
      "76.91.139.18:74\n",
      "116.255.12.184:75\n",
      "128.32.224.18:76\n",
      "96.20.140.58:77\n",
      "88.212.37.169:78\n",
      "109.11.239.168:79\n",
      "95.32.5.235:80\n",
      "2971:81\n",
      "66.29.191.18:82\n",
      "147.32.87.2:83\n",
      "7300:84\n",
      "62.240.166.118:85\n",
      "193.165.4.137:86\n",
      "2739:87\n",
      "86.63.194.225:88\n",
      "113.105.171.56:89\n",
      "118.165.82.114:90\n",
      "68.227.9.121:91\n",
      "53538:92\n",
      "62.24.66.210:93\n",
      "212.235.185.142:94\n",
      "193.87.80.3:95\n",
      "218.43.165.32:96\n",
      "16476:97\n",
      "23739:98\n",
      "79.180.232.121:99\n",
      "208.46.117.171:100\n",
      "147.32.86.147:101\n",
      "194.161.219.176:102\n",
      "udp:103\n",
      "77.72.244.45:104\n",
      "195.24.232.164:105\n",
      "91.207.59.162:106\n",
      "90.183.38.8:107\n",
      "192.84.221.33:108\n",
      "188.95.61.42:109\n",
      "56949:110\n",
      "16775:111\n",
      "95.52.90.246:112\n",
      "2768:113\n",
      "115.184.37.24:114\n",
      "118.233.160.13:115\n",
      "85.117.224.50:116\n",
      "151.50.42.148:117\n",
      "141.156.150.237:118\n",
      "130.236.37.3:119\n",
      "151.41.188.39:120\n",
      "12114:121\n",
      "12748:122\n",
      "147.32.84.118:123\n",
      "74.125.232.220:124\n",
      "113.65.40.102:125\n",
      "46.191.167.153:126\n",
      "147.32.84.8:127\n",
      "94.74.233.93:128\n",
      "212.239.26.199:129\n",
      "62.245.98.34:130\n",
      "74.125.232.202:131\n",
      "147.32.3.12:132\n",
      "196.201.19.50:133\n",
      "43087:134\n",
      "2164:135\n",
      "443:136\n",
      "85.70.149.37:137\n",
      "52948:138\n",
      "122.174.115.150:139\n",
      "194.242.41.77:140\n",
      "85.237.224.48:141\n",
      "83.228.35.75:142\n",
      "70.64.246.26:143\n",
      "77.126.195.83:144\n",
      "81.20.48.51:145\n",
      "147.32.85.88:146\n",
      "81.90.173.232:147\n",
      "147.32.87.30:148\n",
      "130.192.181.149:149\n",
      "205.188.8.254:150\n",
      "82.243.178.156:151\n",
      "18510:152\n",
      "147.213.68.141:153\n",
      "38217:154\n",
      "178.255.217.104:155\n",
      "13723:156\n",
      "6881:157\n",
      "46.127.53.27:158\n",
      "16516:159\n",
      "31.162.200.244:160\n",
      "66.235.132.232:161\n",
      "123:162\n",
      "24211:163\n",
      "83.11.238.15:164\n",
      "147.32.85.103:165\n",
      "201.209.15.135:166\n",
      "173.242.220.227:167\n",
      "119.194.132.184:168\n",
      "41343:169\n",
      "147.32.84.111:170\n",
      "94.100.187.194:171\n",
      "199.59.149.200:172\n",
      "192.221.106.126:173\n",
      "84.38.184.4:174\n",
      "147.32.82.101:175\n",
      "55000:176\n",
      "147.32.86.66:177\n",
      "63231:178\n",
      "93.45.239.29:179\n",
      "77.85.143.253:180\n",
      "89.178.50.15:181\n",
      "51003:182\n",
      "85.207.55.78:183\n",
      "55397:184\n",
      "60.248.145.115:185\n",
      "188.121.222.1:186\n",
      "13631:187\n",
      "80.239.149.26:188\n",
      "81.81.67.46:189\n",
      "147.32.3.51:190\n",
      "41.130.235.95:191\n",
      "82.135.148.158:192\n",
      "79.50.93.42:193\n",
      "147.32.87.22:194\n",
      "74.125.232.219:195\n",
      "2756:196\n",
      "1194:197\n",
      "48190:198\n",
      "194.108.204.22:199\n",
      "147.32.86.77:200\n",
      "115.173.243.205:201\n",
      "84.229.5.224:202\n",
      "2762:203\n",
      "223.205.214.227:204\n",
      "78.90.84.134:205\n",
      "195.72.134.115:206\n",
      "147.32.86.166:207\n",
      "114.26.174.109:208\n",
      "85.14.18.164:209\n",
      "1059:210\n",
      "147.32.87.48:211\n",
      "42796:212\n",
      "1935:213\n",
      "29930:214\n",
      "188.175.127.220:215\n",
      "218.209.43.8:216\n",
      "44146:217\n",
      "147.32.85.56:218\n",
      "89.221.217.12:219\n",
      "16832:220\n",
      "113.161.71.62:221\n",
      "18082:222\n",
      "213.226.63.145:223\n",
      "94.179.103.184:224\n",
      "95.153.189.22:225\n",
      "3605:226\n",
      "1273:227\n",
      "42643:228\n",
      "34588:229\n",
      "8206:230\n",
      "46.10.96.224:231\n",
      "192.166.145.21:232\n",
      "68.51.197.191:233\n",
      "77.120.178.242:234\n",
      "41.241.93.111:235\n",
      "178.2.216.156:236\n",
      "3312:237\n",
      "114.138.217.214:238\n",
      "178.90.23.47:239\n",
      "63550:240\n",
      "122.116.188.88:241\n",
      "88.86.102.50:242\n",
      "147.32.84.229:243\n",
      "60330:244\n",
      "147.32.85.124:245\n",
      "147.32.84.59:246\n",
      "99.141.169.24:247\n",
      "45974:248\n",
      "115.108.130.214:249\n",
      "90.178.130.71:250\n",
      "213.233.154.219:251\n",
      "182.170.250.154:252\n",
      "13873:253\n",
      "213.155.227.215:254\n",
      "130.75.243.145:255\n",
      "68.37.66.192:256\n",
      "201.231.168.71:257\n",
      "80.78.79.156:258\n",
      "147.32.86.252:259\n",
      "69.238.171.67:260\n",
      "34092:261\n",
      "114.45.250.190:262\n",
      "61.219.106.199:263\n",
      "85.193.5.150:264\n",
      "91.123.225.57:265\n",
      "95.172.94.54:266\n",
      "32410:267\n",
      "33791:268\n",
      "31.64.164.71:269\n",
      "41.132.73.182:270\n",
      "77.127.196.107:271\n",
      "94.155.203.122:272\n",
      "122.174.15.39:273\n",
      "82.73.244.56:274\n",
      "183.83.130.244:275\n",
      "59156:276\n",
      "84.222.204.28:277\n",
      "39836:278\n",
      "147.32.192.34:279\n",
      "66.150.244.242:280\n",
      "147.32.86.53:281\n",
      "1942:282\n",
      "195.250.146.6:283\n",
      "3478:284\n",
      "49.240.140.102:285\n",
      "89.223.179.146:286\n",
      "78.141.177.63:287\n",
      "195.113.232.82:288\n",
      "174.48.220.201:289\n",
      "22015:290\n",
      "89.135.152.106:291\n",
      "147.32.85.26:292\n",
      "53185:293\n",
      "50188:294\n",
      "98.166.254.26:295\n",
      "tcp:296\n",
      "49340:297\n",
      "57989:298\n",
      "147.32.85.25:299\n",
      "49230:300\n",
      "161:301\n",
      "205.188.10.189:302\n",
      "24.218.41.238:303\n",
      "178.126.213.97:304\n",
      "188.138.84.239:305\n",
      "147.32.85.60:306\n",
      "92.247.216.178:307\n",
      "74.215.40.251:308\n",
      "14065:309\n",
      "58.182.2.6:310\n",
      "77.246.52.166:311\n",
      "193.6.144.62:312\n",
      "84.12.54.36:313\n",
      "147.32.87.254:314\n",
      "59229:315\n",
      "58676:316\n",
      "2760:317\n",
      "1071:318\n",
      "147.32.86.111:319\n",
      "94.45.56.221:320\n",
      "151.45.215.195:321\n",
      "78.84.137.106:322\n",
      "1153:323\n",
      "64.228.86.17:324\n",
      "77.78.99.22:325\n",
      "21835:326\n",
      "67.218.100.83:327\n",
      "49198:328\n",
      "109.175.50.70:329\n",
      "84.42.148.179:330\n",
      "3389:331\n",
      "43017:332\n",
      "195.110.40.7:333\n",
      "78.128.194.184:334\n",
      "85.132.162.9:335\n",
      "87.244.151.27:336\n",
      "192.100.130.7:337\n",
      "147.32.85.8:338\n",
      "43117:339\n",
      "212.201.86.130:340\n",
      "68.144.201.22:341\n",
      "147.32.86.117:342\n",
      "95.210.161.212:343\n",
      "9146:344\n",
      "91.207.59.161:345\n",
      "193.142.0.1:346\n",
      "23055:347\n",
      "31056:348\n",
      "147.32.86.24:349\n",
      "44593:350\n",
      "147.32.86.223:351\n",
      "5222:352\n",
      "147.32.86.20:353\n",
      "114.40.141.216:354\n",
      "80:355\n",
      "37514:356\n",
      "147.32.87.27:357\n",
      "77.78.99.21:358\n",
      "31002:359\n",
      "147.32.97.253:360\n",
      "147.32.87.220:361\n",
      "81.57.190.106:362\n",
      "55584:363\n",
      "37200:364\n",
      "126.170.234.66:365\n",
      "21348:366\n",
      "194.108.204.19:367\n",
      "94.44.60.103:368\n",
      "113.234.168.192:369\n",
      "147.32.84.164:370\n",
      "147.32.85.34:371\n",
      "188.244.37.212:372\n",
      "1040:373\n",
      "147.32.84.2:374\n",
      "137.254.16.69:375\n",
      "4669:376\n",
      "195.239.66.250:377\n",
      "147.32.84.3:378\n",
      "76.27.46.107:379\n",
      "44076:380\n",
      "34049:381\n",
      "3412:382\n",
      "114.78.14.160:383\n",
      "109.149.84.86:384\n",
      "147.229.74.152:385\n",
      "147.32.86.6:386\n",
      "109.164.3.183:387\n",
      "86.100.133.199:388\n",
      "147.32.89.184:389\n",
      "219.95.99.182:390\n",
      "36165:391\n",
      "2755:392\n",
      "209.85.148.147:393\n",
      "55840:394\n",
      "147.32.86.239:395\n",
      "20992:396\n",
      "74.125.108.208:397\n",
      "82.177.229.240:398\n",
      "78.231.189.116:399\n",
      "67.195.115.177:400\n",
      "52613:401\n",
      "55316:402\n",
      "46.5.184.57:403\n",
      "74.125.232.216:404\n",
      "82.199.111.22:405\n",
      "222.145.103.227:406\n",
      "220.130.40.204:407\n",
      "74.125.232.213:408\n",
      "49463:409\n",
      "3689:410\n",
      "149.5.45.8:411\n",
      "59277:412\n",
      "212.24.150.110:413\n",
      "88.1.124.189:414\n",
      "117.194.42.208:415\n",
      "147.32.84.46:416\n",
      "78.141.181.221:417\n",
      "33482:418\n",
      "147.32.84.94:419\n",
      "212.111.2.151:420\n",
      "993:421\n",
      "87.0.21.115:422\n",
      "85.122.145.220:423\n",
      "147.32.86.110:424\n",
      "147.32.84.73:425\n",
      "49653:426\n",
      "203.23.120.136:427\n",
      "109.153.100.95:428\n",
      "48102:429\n",
      "24.4.101.240:430\n",
      "196.44.240.61:431\n",
      "98.244.73.136:432\n",
      "4628:433\n",
      "8824:434\n",
      "1126:435\n",
      "53:436\n",
      "94.126.186.67:437\n",
      "192.168.1.99:438\n",
      "174.98.117.98:439\n",
      "192.134.164.161:440\n",
      "76.164.192.82:441\n",
      "122.176.204.167:442\n",
      "84.217.37.3:443\n",
      "16041:444\n",
      "60.250.85.109:445\n",
      "24.247.253.8:446\n",
      "3978:447\n",
      "121.218.171.254:448\n",
      "2.159.127.100:449\n",
      "25443:450\n",
      "62.44.1.24:451\n",
      "147.32.85.18:452\n",
      "124.102.16.132:453\n",
      "147.32.86.135:454\n",
      "147.32.80.13:455\n",
      "147.32.85.89:456\n",
      "60.250.102.130:457\n",
      "91.148.14.80:458\n",
      "55557:459\n",
      "81.145.244.43:460\n",
      "50973:461\n",
      "147.32.80.9:462\n",
      "78.80.14.227:463\n",
      "49341:464\n",
      "147.32.85.5:465\n",
      "30657:466\n",
      "77.37.194.251:467\n",
      "147.32.86.181:468\n",
      "23018:469\n",
      "40565:470\n",
      "2774:471\n",
      "213.226.244.55:472\n",
      "63.135.80.58:473\n",
      "178.200.203.145:474\n",
      "147.230.32.193:475\n",
      "82.39.2.249:476\n",
      "147.32.84.184:477\n",
      "147.32.96.45:478\n",
      "94.179.93.205:479\n",
      "90.183.39.86:480\n",
      "82.209.194.12:481\n",
      "62.118.200.4:482\n",
      "58898:483\n",
      "194.129.65.79:484\n",
      "23065:485\n",
      "2.32.222.83:486\n",
      "2.159.25.101:487\n",
      "195.18.192.176:488\n",
      "54239:489\n",
      "213.233.154.226:490\n",
      "116.50.166.74:491\n",
      "26388:492\n",
      "195.250.146.100:493\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import collections\n",
    "import tensorflow as tf\n",
    "\n",
    "def createNeighbor(df):\n",
    "    data = []\n",
    "    for each_line in df.iterrows():\n",
    "        for header in [\"Proto\",\"SrcAddr\",\"Dport\"]:\n",
    "            if header == \"SrcAddr\":\n",
    "                data.append([each_line[1][header],each_line[1][\"DstAddr\"]])\n",
    "                data.append([each_line[1][header],each_line[1][\"Proto\"]])\n",
    "                data.append([each_line[1][header],str(each_line[1][\"Dport\"])])\n",
    "            else:\n",
    "                data.append([str(each_line[1][header]),each_line[1][\"DstAddr\"]])\n",
    "\n",
    "    return data\n",
    "\n",
    "df = pd.read_csv(\"corpus_example.csv\")\n",
    "\n",
    "word2int={}\n",
    "sentences = []\n",
    "wordlist = []\n",
    "for each_line in df.iterrows():\n",
    "    sentences.append(each_line[1].tolist())\n",
    "    for header in [\"Proto\",\"SrcAddr\",\"DstAddr\",\"Dport\"]:\n",
    "        wordlist.append(str(each_line[1][header]))\n",
    "\n",
    "myCounter = collections.Counter(wordlist)\n",
    "print(myCounter.most_common())\n",
    "wordlist=set(wordlist)\n",
    "\n",
    "neighbor = createNeighbor(df)\n",
    "hi = pd.DataFrame(neighbor, columns = ['input', 'label'])\n",
    "\n",
    "for i,word in enumerate(wordlist):\n",
    "    word2int[word] = i\n",
    "\n",
    "for each in word2int.keys():\n",
    "    print(each+\":\"+str(word2int[each]))\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Proto</th>\n",
       "      <th>SrcAddr</th>\n",
       "      <th>DstAddr</th>\n",
       "      <th>Dport</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tcp</td>\n",
       "      <td>93.45.239.29</td>\n",
       "      <td>147.32.84.118</td>\n",
       "      <td>6881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tcp</td>\n",
       "      <td>62.240.166.118</td>\n",
       "      <td>147.32.84.229</td>\n",
       "      <td>13363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>tcp</td>\n",
       "      <td>147.32.86.148</td>\n",
       "      <td>66.235.132.232</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>tcp</td>\n",
       "      <td>147.32.3.51</td>\n",
       "      <td>147.32.84.46</td>\n",
       "      <td>10010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>tcp</td>\n",
       "      <td>88.212.37.169</td>\n",
       "      <td>147.32.84.118</td>\n",
       "      <td>6881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>tcp</td>\n",
       "      <td>94.44.60.103</td>\n",
       "      <td>147.32.84.118</td>\n",
       "      <td>6881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>tcp</td>\n",
       "      <td>2.159.127.100</td>\n",
       "      <td>147.32.84.118</td>\n",
       "      <td>6881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>tcp</td>\n",
       "      <td>213.233.154.219</td>\n",
       "      <td>147.32.84.229</td>\n",
       "      <td>13363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>tcp</td>\n",
       "      <td>88.212.37.169</td>\n",
       "      <td>147.32.84.118</td>\n",
       "      <td>6881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>tcp</td>\n",
       "      <td>95.210.161.212</td>\n",
       "      <td>147.32.84.118</td>\n",
       "      <td>6881</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Proto          SrcAddr         DstAddr  Dport\n",
       "0   tcp     93.45.239.29   147.32.84.118   6881\n",
       "1   tcp   62.240.166.118   147.32.84.229  13363\n",
       "2   tcp    147.32.86.148  66.235.132.232     80\n",
       "3   tcp      147.32.3.51    147.32.84.46  10010\n",
       "4   tcp    88.212.37.169   147.32.84.118   6881\n",
       "5   tcp     94.44.60.103   147.32.84.118   6881\n",
       "6   tcp    2.159.127.100   147.32.84.118   6881\n",
       "7   tcp  213.233.154.219   147.32.84.229  13363\n",
       "8   tcp    88.212.37.169   147.32.84.118   6881\n",
       "9   tcp   95.210.161.212   147.32.84.118   6881"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>input</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>tcp</td>\n",
       "      <td>147.32.84.118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>93.45.239.29</td>\n",
       "      <td>147.32.84.118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>93.45.239.29</td>\n",
       "      <td>tcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>93.45.239.29</td>\n",
       "      <td>6881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6881</td>\n",
       "      <td>147.32.84.118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>tcp</td>\n",
       "      <td>147.32.84.229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>62.240.166.118</td>\n",
       "      <td>147.32.84.229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>62.240.166.118</td>\n",
       "      <td>tcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>62.240.166.118</td>\n",
       "      <td>13363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>13363</td>\n",
       "      <td>147.32.84.229</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            input          label\n",
       "0             tcp  147.32.84.118\n",
       "1    93.45.239.29  147.32.84.118\n",
       "2    93.45.239.29            tcp\n",
       "3    93.45.239.29           6881\n",
       "4            6881  147.32.84.118\n",
       "5             tcp  147.32.84.229\n",
       "6  62.240.166.118  147.32.84.229\n",
       "7  62.240.166.118            tcp\n",
       "8  62.240.166.118          13363\n",
       "9           13363  147.32.84.229"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hi.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ONE_HOT_DIM = len(wordlist)\n",
    "\n",
    "# function to convert numbers to one hot vectors\n",
    "def to_one_hot_encoding(data_point_index):\n",
    "    one_hot_encoding = np.zeros(ONE_HOT_DIM)\n",
    "    one_hot_encoding[data_point_index] = 1\n",
    "    return one_hot_encoding\n",
    "\n",
    "X = [] # input word\n",
    "Y = [] # target word\n",
    "\n",
    "for x, y in zip(hi['input'], hi['label']):\n",
    "    X.append(to_one_hot_encoding(word2int[ x ]))\n",
    "    Y.append(to_one_hot_encoding(word2int[ y ]))\n",
    "\n",
    "# convert them to numpy arrays\n",
    "X_train = np.asarray(X)\n",
    "Y_train = np.asarray(Y)\n",
    "\n",
    "# making placeholders for X_train and Y_train\n",
    "x = tf.placeholder(tf.float32, shape=(None, ONE_HOT_DIM))\n",
    "y_label = tf.placeholder(tf.float32, shape=(None, ONE_HOT_DIM))\n",
    "\n",
    "# word embedding will be 2 dimension for 2d visualization\n",
    "EMBEDDING_DIM = 100\n",
    "\n",
    "# hidden layer: which represents word vector eventually\n",
    "W1 = tf.Variable(tf.random_normal([ONE_HOT_DIM, EMBEDDING_DIM]))\n",
    "b1 = tf.Variable(tf.random_normal([1])) #bias\n",
    "hidden_layer = tf.add(tf.matmul(x,W1), b1)\n",
    "\n",
    "# output layer\n",
    "W2 = tf.Variable(tf.random_normal([EMBEDDING_DIM, ONE_HOT_DIM]))\n",
    "b2 = tf.Variable(tf.random_normal([1]))\n",
    "prediction = tf.nn.softmax(tf.add( tf.matmul(hidden_layer, W2), b2))\n",
    "\n",
    "# loss function: cross entropy\n",
    "loss = tf.reduce_mean(-tf.reduce_sum(y_label * tf.log(prediction), axis=[1]))\n",
    "\n",
    "# training operation\n",
    "train_op = tf.train.GradientDescentOptimizer(0.05).minimize(loss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 loss is :  29.304575\n",
      "iteration 1 loss is :  28.655039\n",
      "iteration 2 loss is :  28.348558\n",
      "iteration 3 loss is :  28.032267\n",
      "iteration 4 loss is :  27.783314\n",
      "iteration 5 loss is :  27.535303\n",
      "iteration 6 loss is :  27.384508\n",
      "iteration 7 loss is :  27.198217\n",
      "iteration 8 loss is :  27.222286\n",
      "iteration 9 loss is :  27.014547\n",
      "iteration 10 loss is :  27.137928\n",
      "iteration 11 loss is :  26.814697\n",
      "iteration 12 loss is :  26.93451\n",
      "iteration 13 loss is :  26.53341\n",
      "iteration 14 loss is :  26.618729\n",
      "iteration 15 loss is :  26.21677\n",
      "iteration 16 loss is :  26.248806\n",
      "iteration 17 loss is :  25.896444\n",
      "iteration 18 loss is :  25.892992\n",
      "iteration 19 loss is :  25.595936\n",
      "iteration 20 loss is :  25.58899\n",
      "iteration 21 loss is :  25.330856\n",
      "iteration 22 loss is :  25.343502\n",
      "iteration 23 loss is :  25.10374\n",
      "iteration 24 loss is :  25.147343\n",
      "iteration 25 loss is :  24.906683\n",
      "iteration 26 loss is :  24.982069\n",
      "iteration 27 loss is :  24.725573\n",
      "iteration 28 loss is :  24.823338\n",
      "iteration 29 loss is :  24.544838\n",
      "iteration 30 loss is :  24.647724\n",
      "iteration 31 loss is :  24.352549\n",
      "iteration 32 loss is :  24.442074\n",
      "iteration 33 loss is :  24.143652\n",
      "iteration 34 loss is :  24.206337\n",
      "iteration 35 loss is :  23.919151\n",
      "iteration 36 loss is :  23.949816\n",
      "iteration 37 loss is :  23.68412\n",
      "iteration 38 loss is :  23.68566\n",
      "iteration 39 loss is :  23.446402\n",
      "iteration 40 loss is :  23.4273\n",
      "iteration 41 loss is :  23.21513\n",
      "iteration 42 loss is :  23.18672\n",
      "iteration 43 loss is :  22.998537\n",
      "iteration 44 loss is :  22.972244\n",
      "iteration 45 loss is :  22.801905\n",
      "iteration 46 loss is :  22.788128\n",
      "iteration 47 loss is :  22.627722\n",
      "iteration 48 loss is :  22.635792\n",
      "iteration 49 loss is :  22.476076\n",
      "iteration 50 loss is :  22.51428\n",
      "iteration 51 loss is :  22.344336\n",
      "iteration 52 loss is :  22.41769\n",
      "iteration 53 loss is :  22.225342\n",
      "iteration 54 loss is :  22.331535\n",
      "iteration 55 loss is :  22.106813\n",
      "iteration 56 loss is :  22.232565\n",
      "iteration 57 loss is :  21.973179\n",
      "iteration 58 loss is :  22.095968\n",
      "iteration 59 loss is :  21.812048\n",
      "iteration 60 loss is :  21.90756\n",
      "iteration 61 loss is :  21.620478\n",
      "iteration 62 loss is :  21.67187\n",
      "iteration 63 loss is :  21.406769\n",
      "iteration 64 loss is :  21.410114\n",
      "iteration 65 loss is :  21.186195\n",
      "iteration 66 loss is :  21.150126\n",
      "iteration 67 loss is :  20.973322\n",
      "iteration 68 loss is :  20.913244\n",
      "iteration 69 loss is :  20.777533\n",
      "iteration 70 loss is :  20.708542\n",
      "iteration 71 loss is :  20.603123\n",
      "iteration 72 loss is :  20.53539\n",
      "iteration 73 loss is :  20.450806\n",
      "iteration 74 loss is :  20.38966\n",
      "iteration 75 loss is :  20.31997\n",
      "iteration 76 loss is :  20.268084\n",
      "iteration 77 loss is :  20.210527\n",
      "iteration 78 loss is :  20.17039\n",
      "iteration 79 loss is :  20.124113\n",
      "iteration 80 loss is :  20.099619\n",
      "iteration 81 loss is :  20.064419\n",
      "iteration 82 loss is :  20.061737\n",
      "iteration 83 loss is :  20.035397\n",
      "iteration 84 loss is :  20.062473\n",
      "iteration 85 loss is :  20.037144\n",
      "iteration 86 loss is :  20.099476\n",
      "iteration 87 loss is :  20.059872\n",
      "iteration 88 loss is :  20.151371\n",
      "iteration 89 loss is :  20.080421\n",
      "iteration 90 loss is :  20.176859\n",
      "iteration 91 loss is :  20.066607\n",
      "iteration 92 loss is :  20.133322\n",
      "iteration 93 loss is :  19.986391\n",
      "iteration 94 loss is :  19.996807\n",
      "iteration 95 loss is :  19.824554\n",
      "iteration 96 loss is :  19.774872\n",
      "iteration 97 loss is :  19.600056\n",
      "iteration 98 loss is :  19.511318\n",
      "iteration 99 loss is :  19.359407\n",
      "iteration 100 loss is :  19.262228\n",
      "iteration 101 loss is :  19.144117\n",
      "iteration 102 loss is :  19.058956\n",
      "iteration 103 loss is :  18.97\n",
      "iteration 104 loss is :  18.901575\n",
      "iteration 105 loss is :  18.832659\n",
      "iteration 106 loss is :  18.778109\n",
      "iteration 107 loss is :  18.722292\n",
      "iteration 108 loss is :  18.678478\n",
      "iteration 109 loss is :  18.632011\n",
      "iteration 110 loss is :  18.59775\n",
      "iteration 111 loss is :  18.55923\n",
      "iteration 112 loss is :  18.53559\n",
      "iteration 113 loss is :  18.505058\n",
      "iteration 114 loss is :  18.49539\n",
      "iteration 115 loss is :  18.473463\n",
      "iteration 116 loss is :  18.483706\n",
      "iteration 117 loss is :  18.470322\n",
      "iteration 118 loss is :  18.508749\n",
      "iteration 119 loss is :  18.500975\n",
      "iteration 120 loss is :  18.576014\n",
      "iteration 121 loss is :  18.566257\n",
      "iteration 122 loss is :  18.679808\n",
      "iteration 123 loss is :  18.657703\n",
      "iteration 124 loss is :  18.794943\n",
      "iteration 125 loss is :  18.750547\n",
      "iteration 126 loss is :  18.87509\n",
      "iteration 127 loss is :  18.794758\n",
      "iteration 128 loss is :  18.857544\n",
      "iteration 129 loss is :  18.72304\n",
      "iteration 130 loss is :  18.687\n",
      "iteration 131 loss is :  18.496592\n",
      "iteration 132 loss is :  18.368195\n",
      "iteration 133 loss is :  18.163132\n",
      "iteration 134 loss is :  18.005728\n",
      "iteration 135 loss is :  17.847052\n",
      "iteration 136 loss is :  17.725176\n",
      "iteration 137 loss is :  17.626638\n",
      "iteration 138 loss is :  17.548893\n",
      "iteration 139 loss is :  17.485954\n",
      "iteration 140 loss is :  17.432207\n",
      "iteration 141 loss is :  17.385027\n",
      "iteration 142 loss is :  17.34193\n",
      "iteration 143 loss is :  17.301872\n",
      "iteration 144 loss is :  17.263958\n",
      "iteration 145 loss is :  17.227827\n",
      "iteration 146 loss is :  17.193123\n",
      "iteration 147 loss is :  17.159828\n",
      "iteration 148 loss is :  17.127848\n",
      "iteration 149 loss is :  17.097445\n",
      "iteration 150 loss is :  17.06862\n",
      "iteration 151 loss is :  17.042002\n",
      "iteration 152 loss is :  17.017769\n",
      "iteration 153 loss is :  16.997139\n",
      "iteration 154 loss is :  16.980648\n",
      "iteration 155 loss is :  16.970572\n",
      "iteration 156 loss is :  16.968319\n",
      "iteration 157 loss is :  16.976896\n",
      "iteration 158 loss is :  17.001074\n",
      "iteration 159 loss is :  17.038763\n",
      "iteration 160 loss is :  17.10887\n",
      "iteration 161 loss is :  17.176577\n",
      "iteration 162 loss is :  17.309565\n",
      "iteration 163 loss is :  17.376617\n",
      "iteration 164 loss is :  17.554533\n",
      "iteration 165 loss is :  17.570078\n",
      "iteration 166 loss is :  17.728493\n",
      "iteration 167 loss is :  17.665085\n",
      "iteration 168 loss is :  17.7324\n",
      "iteration 169 loss is :  17.584393\n",
      "iteration 170 loss is :  17.523148\n",
      "iteration 171 loss is :  17.319471\n",
      "iteration 172 loss is :  17.163897\n",
      "iteration 173 loss is :  16.977076\n",
      "iteration 174 loss is :  16.821829\n",
      "iteration 175 loss is :  16.695993\n",
      "iteration 176 loss is :  16.58979\n",
      "iteration 177 loss is :  16.513927\n",
      "iteration 178 loss is :  16.447449\n",
      "iteration 179 loss is :  16.398436\n",
      "iteration 180 loss is :  16.353537\n",
      "iteration 181 loss is :  16.317757\n",
      "iteration 182 loss is :  16.284096\n",
      "iteration 183 loss is :  16.255672\n",
      "iteration 184 loss is :  16.22882\n",
      "iteration 185 loss is :  16.20557\n",
      "iteration 186 loss is :  16.18418\n",
      "iteration 187 loss is :  16.165813\n",
      "iteration 188 loss is :  16.150295\n",
      "iteration 189 loss is :  16.137506\n",
      "iteration 190 loss is :  16.129435\n",
      "iteration 191 loss is :  16.123583\n",
      "iteration 192 loss is :  16.125587\n",
      "iteration 193 loss is :  16.127626\n",
      "iteration 194 loss is :  16.142588\n",
      "iteration 195 loss is :  16.151512\n",
      "iteration 196 loss is :  16.180786\n",
      "iteration 197 loss is :  16.191566\n",
      "iteration 198 loss is :  16.231998\n",
      "iteration 199 loss is :  16.235426\n",
      "iteration 200 loss is :  16.277514\n",
      "iteration 201 loss is :  16.263535\n",
      "iteration 202 loss is :  16.294033\n",
      "iteration 203 loss is :  16.256884\n",
      "iteration 204 loss is :  16.264814\n",
      "iteration 205 loss is :  16.20578\n",
      "iteration 206 loss is :  16.18828\n",
      "iteration 207 loss is :  16.114733\n",
      "iteration 208 loss is :  16.078249\n",
      "iteration 209 loss is :  16.000414\n",
      "iteration 210 loss is :  15.956232\n",
      "iteration 211 loss is :  15.883031\n",
      "iteration 212 loss is :  15.840435\n",
      "iteration 213 loss is :  15.776848\n",
      "iteration 214 loss is :  15.740282\n",
      "iteration 215 loss is :  15.687325\n",
      "iteration 216 loss is :  15.657467\n",
      "iteration 217 loss is :  15.613853\n",
      "iteration 218 loss is :  15.58988\n",
      "iteration 219 loss is :  15.553641\n",
      "iteration 220 loss is :  15.53457\n",
      "iteration 221 loss is :  15.503959\n",
      "iteration 222 loss is :  15.489085\n",
      "iteration 223 loss is :  15.462796\n",
      "iteration 224 loss is :  15.451813\n",
      "iteration 225 loss is :  15.428923\n",
      "iteration 226 loss is :  15.4218\n",
      "iteration 227 loss is :  15.401608\n",
      "iteration 228 loss is :  15.398407\n",
      "iteration 229 loss is :  15.380311\n",
      "iteration 230 loss is :  15.381161\n",
      "iteration 231 loss is :  15.364354\n",
      "iteration 232 loss is :  15.36911\n",
      "iteration 233 loss is :  15.3526535\n",
      "iteration 234 loss is :  15.360718\n",
      "iteration 235 loss is :  15.343276\n",
      "iteration 236 loss is :  15.353396\n",
      "iteration 237 loss is :  15.333495\n",
      "iteration 238 loss is :  15.343897\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 239 loss is :  15.320094\n",
      "iteration 240 loss is :  15.32864\n",
      "iteration 241 loss is :  15.299979\n",
      "iteration 242 loss is :  15.304809\n",
      "iteration 243 loss is :  15.271204\n",
      "iteration 244 loss is :  15.271186\n",
      "iteration 245 loss is :  15.23339\n",
      "iteration 246 loss is :  15.228471\n",
      "iteration 247 loss is :  15.188103\n",
      "iteration 248 loss is :  15.179175\n",
      "iteration 249 loss is :  15.138198\n",
      "iteration 250 loss is :  15.12668\n",
      "iteration 251 loss is :  15.08688\n",
      "iteration 252 loss is :  15.074278\n",
      "iteration 253 loss is :  15.036932\n",
      "iteration 254 loss is :  15.024534\n",
      "iteration 255 loss is :  14.990325\n",
      "iteration 256 loss is :  14.978995\n",
      "iteration 257 loss is :  14.948099\n",
      "iteration 258 loss is :  14.938421\n",
      "iteration 259 loss is :  14.910652\n",
      "iteration 260 loss is :  14.903017\n",
      "iteration 261 loss is :  14.878063\n",
      "iteration 262 loss is :  14.872705\n",
      "iteration 263 loss is :  14.850198\n",
      "iteration 264 loss is :  14.847293\n",
      "iteration 265 loss is :  14.826789\n",
      "iteration 266 loss is :  14.826409\n",
      "iteration 267 loss is :  14.807488\n",
      "iteration 268 loss is :  14.809609\n",
      "iteration 269 loss is :  14.791694\n",
      "iteration 270 loss is :  14.79608\n",
      "iteration 271 loss is :  14.778497\n",
      "iteration 272 loss is :  14.784646\n",
      "iteration 273 loss is :  14.766706\n",
      "iteration 274 loss is :  14.773779\n",
      "iteration 275 loss is :  14.754628\n",
      "iteration 276 loss is :  14.761526\n",
      "iteration 277 loss is :  14.740459\n",
      "iteration 278 loss is :  14.745984\n",
      "iteration 279 loss is :  14.722421\n",
      "iteration 280 loss is :  14.725504\n",
      "iteration 281 loss is :  14.699255\n",
      "iteration 282 loss is :  14.699131\n",
      "iteration 283 loss is :  14.6704035\n",
      "iteration 284 loss is :  14.666922\n",
      "iteration 285 loss is :  14.636381\n",
      "iteration 286 loss is :  14.629855\n",
      "iteration 287 loss is :  14.598461\n",
      "iteration 288 loss is :  14.589656\n",
      "iteration 289 loss is :  14.558416\n",
      "iteration 290 loss is :  14.548262\n",
      "iteration 291 loss is :  14.518139\n",
      "iteration 292 loss is :  14.5075655\n",
      "iteration 293 loss is :  14.479227\n",
      "iteration 294 loss is :  14.468986\n",
      "iteration 295 loss is :  14.442822\n",
      "iteration 296 loss is :  14.433415\n",
      "iteration 297 loss is :  14.409603\n",
      "iteration 298 loss is :  14.401342\n",
      "iteration 299 loss is :  14.379798\n",
      "iteration 300 loss is :  14.372857\n",
      "iteration 301 loss is :  14.35338\n",
      "iteration 302 loss is :  14.34772\n",
      "iteration 303 loss is :  14.33009\n",
      "iteration 304 loss is :  14.325531\n",
      "iteration 305 loss is :  14.309396\n",
      "iteration 306 loss is :  14.3056965\n",
      "iteration 307 loss is :  14.290667\n",
      "iteration 308 loss is :  14.28734\n",
      "iteration 309 loss is :  14.272979\n",
      "iteration 310 loss is :  14.269491\n",
      "iteration 311 loss is :  14.25534\n",
      "iteration 312 loss is :  14.2510605\n",
      "iteration 313 loss is :  14.236679\n",
      "iteration 314 loss is :  14.230982\n",
      "iteration 315 loss is :  14.216014\n",
      "iteration 316 loss is :  14.2084055\n",
      "iteration 317 loss is :  14.192631\n",
      "iteration 318 loss is :  14.182811\n",
      "iteration 319 loss is :  14.16617\n",
      "iteration 320 loss is :  14.154152\n",
      "iteration 321 loss is :  14.136819\n",
      "iteration 322 loss is :  14.122816\n",
      "iteration 323 loss is :  14.105112\n",
      "iteration 324 loss is :  14.089583\n",
      "iteration 325 loss is :  14.071909\n",
      "iteration 326 loss is :  14.055411\n",
      "iteration 327 loss is :  14.038208\n",
      "iteration 328 loss is :  14.021299\n",
      "iteration 329 loss is :  14.004919\n",
      "iteration 330 loss is :  13.98808\n",
      "iteration 331 loss is :  13.972854\n",
      "iteration 332 loss is :  13.956408\n",
      "iteration 333 loss is :  13.942517\n",
      "iteration 334 loss is :  13.926698\n",
      "iteration 335 loss is :  13.914274\n",
      "iteration 336 loss is :  13.899139\n",
      "iteration 337 loss is :  13.888214\n",
      "iteration 338 loss is :  13.873733\n",
      "iteration 339 loss is :  13.86428\n",
      "iteration 340 loss is :  13.850392\n",
      "iteration 341 loss is :  13.842334\n",
      "iteration 342 loss is :  13.828832\n",
      "iteration 343 loss is :  13.822081\n",
      "iteration 344 loss is :  13.808732\n",
      "iteration 345 loss is :  13.803143\n",
      "iteration 346 loss is :  13.789667\n",
      "iteration 347 loss is :  13.785067\n",
      "iteration 348 loss is :  13.771116\n",
      "iteration 349 loss is :  13.7673235\n",
      "iteration 350 loss is :  13.75262\n",
      "iteration 351 loss is :  13.749364\n",
      "iteration 352 loss is :  13.733618\n",
      "iteration 353 loss is :  13.730725\n",
      "iteration 354 loss is :  13.7137165\n",
      "iteration 355 loss is :  13.711006\n",
      "iteration 356 loss is :  13.692633\n",
      "iteration 357 loss is :  13.689946\n",
      "iteration 358 loss is :  13.670202\n",
      "iteration 359 loss is :  13.66746\n",
      "iteration 360 loss is :  13.646482\n",
      "iteration 361 loss is :  13.64371\n",
      "iteration 362 loss is :  13.621703\n",
      "iteration 363 loss is :  13.6189575\n",
      "iteration 364 loss is :  13.596182\n",
      "iteration 365 loss is :  13.593562\n",
      "iteration 366 loss is :  13.570317\n",
      "iteration 367 loss is :  13.56798\n",
      "iteration 368 loss is :  13.544471\n",
      "iteration 369 loss is :  13.542622\n",
      "iteration 370 loss is :  13.519048\n",
      "iteration 371 loss is :  13.517804\n",
      "iteration 372 loss is :  13.494328\n",
      "iteration 373 loss is :  13.493825\n",
      "iteration 374 loss is :  13.470451\n",
      "iteration 375 loss is :  13.470815\n",
      "iteration 376 loss is :  13.447569\n",
      "iteration 377 loss is :  13.4488535\n",
      "iteration 378 loss is :  13.425636\n",
      "iteration 379 loss is :  13.427919\n",
      "iteration 380 loss is :  13.40461\n",
      "iteration 381 loss is :  13.407916\n",
      "iteration 382 loss is :  13.384357\n",
      "iteration 383 loss is :  13.388674\n",
      "iteration 384 loss is :  13.364696\n",
      "iteration 385 loss is :  13.369969\n",
      "iteration 386 loss is :  13.345389\n",
      "iteration 387 loss is :  13.35156\n",
      "iteration 388 loss is :  13.326224\n",
      "iteration 389 loss is :  13.3332405\n",
      "iteration 390 loss is :  13.307003\n",
      "iteration 391 loss is :  13.314753\n",
      "iteration 392 loss is :  13.287535\n",
      "iteration 393 loss is :  13.295933\n",
      "iteration 394 loss is :  13.2676735\n",
      "iteration 395 loss is :  13.276619\n",
      "iteration 396 loss is :  13.247343\n",
      "iteration 397 loss is :  13.2567835\n",
      "iteration 398 loss is :  13.226545\n",
      "iteration 399 loss is :  13.236456\n",
      "iteration 400 loss is :  13.205353\n",
      "iteration 401 loss is :  13.215708\n",
      "iteration 402 loss is :  13.183873\n",
      "iteration 403 loss is :  13.19468\n",
      "iteration 404 loss is :  13.162233\n",
      "iteration 405 loss is :  13.173552\n",
      "iteration 406 loss is :  13.140599\n",
      "iteration 407 loss is :  13.152465\n",
      "iteration 408 loss is :  13.119111\n",
      "iteration 409 loss is :  13.131611\n",
      "iteration 410 loss is :  13.097921\n",
      "iteration 411 loss is :  13.111147\n",
      "iteration 412 loss is :  13.0771265\n",
      "iteration 413 loss is :  13.091144\n",
      "iteration 414 loss is :  13.056788\n",
      "iteration 415 loss is :  13.071666\n",
      "iteration 416 loss is :  13.036937\n",
      "iteration 417 loss is :  13.052767\n",
      "iteration 418 loss is :  13.017581\n",
      "iteration 419 loss is :  13.034408\n",
      "iteration 420 loss is :  12.998671\n",
      "iteration 421 loss is :  13.016521\n",
      "iteration 422 loss is :  12.980155\n",
      "iteration 423 loss is :  12.999062\n",
      "iteration 424 loss is :  12.961952\n",
      "iteration 425 loss is :  12.981891\n",
      "iteration 426 loss is :  12.943953\n",
      "iteration 427 loss is :  12.964912\n",
      "iteration 428 loss is :  12.926081\n",
      "iteration 429 loss is :  12.948014\n",
      "iteration 430 loss is :  12.908246\n",
      "iteration 431 loss is :  12.931088\n",
      "iteration 432 loss is :  12.890361\n",
      "iteration 433 loss is :  12.914051\n",
      "iteration 434 loss is :  12.87238\n",
      "iteration 435 loss is :  12.896836\n",
      "iteration 436 loss is :  12.854253\n",
      "iteration 437 loss is :  12.879389\n",
      "iteration 438 loss is :  12.835977\n",
      "iteration 439 loss is :  12.861725\n",
      "iteration 440 loss is :  12.817551\n",
      "iteration 441 loss is :  12.843849\n",
      "iteration 442 loss is :  12.799022\n",
      "iteration 443 loss is :  12.825796\n",
      "iteration 444 loss is :  12.780396\n",
      "iteration 445 loss is :  12.807618\n",
      "iteration 446 loss is :  12.761715\n",
      "iteration 447 loss is :  12.789339\n",
      "iteration 448 loss is :  12.743027\n",
      "iteration 449 loss is :  12.77105\n",
      "iteration 450 loss is :  12.724379\n",
      "iteration 451 loss is :  12.752762\n",
      "iteration 452 loss is :  12.705783\n",
      "iteration 453 loss is :  12.7345085\n",
      "iteration 454 loss is :  12.687278\n",
      "iteration 455 loss is :  12.716332\n",
      "iteration 456 loss is :  12.6688595\n",
      "iteration 457 loss is :  12.698262\n",
      "iteration 458 loss is :  12.65054\n",
      "iteration 459 loss is :  12.680257\n",
      "iteration 460 loss is :  12.632308\n",
      "iteration 461 loss is :  12.662354\n",
      "iteration 462 loss is :  12.614151\n",
      "iteration 463 loss is :  12.644513\n",
      "iteration 464 loss is :  12.596084\n",
      "iteration 465 loss is :  12.626732\n",
      "iteration 466 loss is :  12.578055\n",
      "iteration 467 loss is :  12.608991\n",
      "iteration 468 loss is :  12.560073\n",
      "iteration 469 loss is :  12.591299\n",
      "iteration 470 loss is :  12.542139\n",
      "iteration 471 loss is :  12.573628\n",
      "iteration 472 loss is :  12.524211\n",
      "iteration 473 loss is :  12.55598\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 474 loss is :  12.506328\n",
      "iteration 475 loss is :  12.538346\n",
      "iteration 476 loss is :  12.488459\n",
      "iteration 477 loss is :  12.520744\n",
      "iteration 478 loss is :  12.470616\n",
      "iteration 479 loss is :  12.503181\n",
      "iteration 480 loss is :  12.452816\n",
      "iteration 481 loss is :  12.485646\n",
      "iteration 482 loss is :  12.435057\n",
      "iteration 483 loss is :  12.468174\n",
      "iteration 484 loss is :  12.417347\n",
      "iteration 485 loss is :  12.4507475\n",
      "iteration 486 loss is :  12.399701\n",
      "iteration 487 loss is :  12.433412\n",
      "iteration 488 loss is :  12.382109\n",
      "iteration 489 loss is :  12.416142\n",
      "iteration 490 loss is :  12.364581\n",
      "iteration 491 loss is :  12.398951\n",
      "iteration 492 loss is :  12.347124\n",
      "iteration 493 loss is :  12.381856\n",
      "iteration 494 loss is :  12.329747\n",
      "iteration 495 loss is :  12.364852\n",
      "iteration 496 loss is :  12.312433\n",
      "iteration 497 loss is :  12.3479185\n",
      "iteration 498 loss is :  12.29519\n",
      "iteration 499 loss is :  12.331086\n",
      "iteration 500 loss is :  12.278007\n",
      "iteration 501 loss is :  12.31432\n",
      "iteration 502 loss is :  12.26088\n",
      "iteration 503 loss is :  12.297631\n",
      "iteration 504 loss is :  12.243837\n",
      "iteration 505 loss is :  12.281024\n",
      "iteration 506 loss is :  12.226837\n",
      "iteration 507 loss is :  12.2644825\n",
      "iteration 508 loss is :  12.209886\n",
      "iteration 509 loss is :  12.248001\n",
      "iteration 510 loss is :  12.192993\n",
      "iteration 511 loss is :  12.231581\n",
      "iteration 512 loss is :  12.176138\n",
      "iteration 513 loss is :  12.215244\n",
      "iteration 514 loss is :  12.159348\n",
      "iteration 515 loss is :  12.198925\n",
      "iteration 516 loss is :  12.142596\n",
      "iteration 517 loss is :  12.182692\n",
      "iteration 518 loss is :  12.125889\n",
      "iteration 519 loss is :  12.166487\n",
      "iteration 520 loss is :  12.109224\n",
      "iteration 521 loss is :  12.150359\n",
      "iteration 522 loss is :  12.0925865\n",
      "iteration 523 loss is :  12.13428\n",
      "iteration 524 loss is :  12.076009\n",
      "iteration 525 loss is :  12.118239\n",
      "iteration 526 loss is :  12.059473\n",
      "iteration 527 loss is :  12.102263\n",
      "iteration 528 loss is :  12.042981\n",
      "iteration 529 loss is :  12.086336\n",
      "iteration 530 loss is :  12.026536\n",
      "iteration 531 loss is :  12.070465\n",
      "iteration 532 loss is :  12.010133\n",
      "iteration 533 loss is :  12.054651\n",
      "iteration 534 loss is :  11.993779\n",
      "iteration 535 loss is :  12.038894\n",
      "iteration 536 loss is :  11.977465\n",
      "iteration 537 loss is :  12.023176\n",
      "iteration 538 loss is :  11.961192\n",
      "iteration 539 loss is :  12.007505\n",
      "iteration 540 loss is :  11.944971\n",
      "iteration 541 loss is :  11.991893\n",
      "iteration 542 loss is :  11.928785\n",
      "iteration 543 loss is :  11.976337\n",
      "iteration 544 loss is :  11.912641\n",
      "iteration 545 loss is :  11.960823\n",
      "iteration 546 loss is :  11.896536\n",
      "iteration 547 loss is :  11.94536\n",
      "iteration 548 loss is :  11.880482\n",
      "iteration 549 loss is :  11.9299555\n",
      "iteration 550 loss is :  11.864456\n",
      "iteration 551 loss is :  11.914581\n",
      "iteration 552 loss is :  11.848481\n",
      "iteration 553 loss is :  11.89927\n",
      "iteration 554 loss is :  11.832538\n",
      "iteration 555 loss is :  11.884001\n",
      "iteration 556 loss is :  11.816637\n",
      "iteration 557 loss is :  11.868775\n",
      "iteration 558 loss is :  11.800783\n",
      "iteration 559 loss is :  11.853606\n",
      "iteration 560 loss is :  11.784968\n",
      "iteration 561 loss is :  11.838475\n",
      "iteration 562 loss is :  11.769191\n",
      "iteration 563 loss is :  11.823392\n",
      "iteration 564 loss is :  11.753452\n",
      "iteration 565 loss is :  11.808359\n",
      "iteration 566 loss is :  11.737768\n",
      "iteration 567 loss is :  11.793383\n",
      "iteration 568 loss is :  11.722128\n",
      "iteration 569 loss is :  11.778454\n",
      "iteration 570 loss is :  11.706533\n",
      "iteration 571 loss is :  11.763571\n",
      "iteration 572 loss is :  11.690966\n",
      "iteration 573 loss is :  11.748767\n",
      "iteration 574 loss is :  11.675461\n",
      "iteration 575 loss is :  11.733969\n",
      "iteration 576 loss is :  11.6599865\n",
      "iteration 577 loss is :  11.719243\n",
      "iteration 578 loss is :  11.644564\n",
      "iteration 579 loss is :  11.704566\n",
      "iteration 580 loss is :  11.629177\n",
      "iteration 581 loss is :  11.689926\n",
      "iteration 582 loss is :  11.61386\n",
      "iteration 583 loss is :  11.675335\n",
      "iteration 584 loss is :  11.598559\n",
      "iteration 585 loss is :  11.66079\n",
      "iteration 586 loss is :  11.583322\n",
      "iteration 587 loss is :  11.646276\n",
      "iteration 588 loss is :  11.568122\n",
      "iteration 589 loss is :  11.631834\n",
      "iteration 590 loss is :  11.5529785\n",
      "iteration 591 loss is :  11.617438\n",
      "iteration 592 loss is :  11.537866\n",
      "iteration 593 loss is :  11.603075\n",
      "iteration 594 loss is :  11.522802\n",
      "iteration 595 loss is :  11.588763\n",
      "iteration 596 loss is :  11.507791\n",
      "iteration 597 loss is :  11.574498\n",
      "iteration 598 loss is :  11.49283\n",
      "iteration 599 loss is :  11.560257\n",
      "iteration 600 loss is :  11.477906\n",
      "iteration 601 loss is :  11.546074\n",
      "iteration 602 loss is :  11.463023\n",
      "iteration 603 loss is :  11.531934\n",
      "iteration 604 loss is :  11.448207\n",
      "iteration 605 loss is :  11.517822\n",
      "iteration 606 loss is :  11.433404\n",
      "iteration 607 loss is :  11.5037365\n",
      "iteration 608 loss is :  11.418647\n",
      "iteration 609 loss is :  11.489685\n",
      "iteration 610 loss is :  11.403945\n",
      "iteration 611 loss is :  11.475669\n",
      "iteration 612 loss is :  11.389286\n",
      "iteration 613 loss is :  11.461689\n",
      "iteration 614 loss is :  11.374648\n",
      "iteration 615 loss is :  11.447724\n",
      "iteration 616 loss is :  11.360065\n",
      "iteration 617 loss is :  11.433787\n",
      "iteration 618 loss is :  11.345516\n",
      "iteration 619 loss is :  11.419864\n",
      "iteration 620 loss is :  11.331014\n",
      "iteration 621 loss is :  11.405971\n",
      "iteration 622 loss is :  11.3165455\n",
      "iteration 623 loss is :  11.392091\n",
      "iteration 624 loss is :  11.302111\n",
      "iteration 625 loss is :  11.378243\n",
      "iteration 626 loss is :  11.28771\n",
      "iteration 627 loss is :  11.364398\n",
      "iteration 628 loss is :  11.273362\n",
      "iteration 629 loss is :  11.350599\n",
      "iteration 630 loss is :  11.259049\n",
      "iteration 631 loss is :  11.336813\n",
      "iteration 632 loss is :  11.244763\n",
      "iteration 633 loss is :  11.323035\n",
      "iteration 634 loss is :  11.230513\n",
      "iteration 635 loss is :  11.309275\n",
      "iteration 636 loss is :  11.216304\n",
      "iteration 637 loss is :  11.295544\n",
      "iteration 638 loss is :  11.202145\n",
      "iteration 639 loss is :  11.281843\n",
      "iteration 640 loss is :  11.188036\n",
      "iteration 641 loss is :  11.268155\n",
      "iteration 642 loss is :  11.173961\n",
      "iteration 643 loss is :  11.254506\n",
      "iteration 644 loss is :  11.159935\n",
      "iteration 645 loss is :  11.240909\n",
      "iteration 646 loss is :  11.145965\n",
      "iteration 647 loss is :  11.22733\n",
      "iteration 648 loss is :  11.132037\n",
      "iteration 649 loss is :  11.213792\n",
      "iteration 650 loss is :  11.118149\n",
      "iteration 651 loss is :  11.200289\n",
      "iteration 652 loss is :  11.104324\n",
      "iteration 653 loss is :  11.186832\n",
      "iteration 654 loss is :  11.090551\n",
      "iteration 655 loss is :  11.173425\n",
      "iteration 656 loss is :  11.0768385\n",
      "iteration 657 loss is :  11.160053\n",
      "iteration 658 loss is :  11.063161\n",
      "iteration 659 loss is :  11.146708\n",
      "iteration 660 loss is :  11.049536\n",
      "iteration 661 loss is :  11.133426\n",
      "iteration 662 loss is :  11.035982\n",
      "iteration 663 loss is :  11.120191\n",
      "iteration 664 loss is :  11.02246\n",
      "iteration 665 loss is :  11.107\n",
      "iteration 666 loss is :  11.009006\n",
      "iteration 667 loss is :  11.093857\n",
      "iteration 668 loss is :  10.995597\n",
      "iteration 669 loss is :  11.080759\n",
      "iteration 670 loss is :  10.982239\n",
      "iteration 671 loss is :  11.067694\n",
      "iteration 672 loss is :  10.96892\n",
      "iteration 673 loss is :  11.0546875\n",
      "iteration 674 loss is :  10.955665\n",
      "iteration 675 loss is :  11.041708\n",
      "iteration 676 loss is :  10.942444\n",
      "iteration 677 loss is :  11.028774\n",
      "iteration 678 loss is :  10.929279\n",
      "iteration 679 loss is :  11.015886\n",
      "iteration 680 loss is :  10.916152\n",
      "iteration 681 loss is :  11.003009\n",
      "iteration 682 loss is :  10.903074\n",
      "iteration 683 loss is :  10.990185\n",
      "iteration 684 loss is :  10.890021\n",
      "iteration 685 loss is :  10.977406\n",
      "iteration 686 loss is :  10.877024\n",
      "iteration 687 loss is :  10.964623\n",
      "iteration 688 loss is :  10.864046\n",
      "iteration 689 loss is :  10.951873\n",
      "iteration 690 loss is :  10.851109\n",
      "iteration 691 loss is :  10.939159\n",
      "iteration 692 loss is :  10.83821\n",
      "iteration 693 loss is :  10.926478\n",
      "iteration 694 loss is :  10.825344\n",
      "iteration 695 loss is :  10.913797\n",
      "iteration 696 loss is :  10.812504\n",
      "iteration 697 loss is :  10.901149\n",
      "iteration 698 loss is :  10.799692\n",
      "iteration 699 loss is :  10.888524\n",
      "iteration 700 loss is :  10.786918\n",
      "iteration 701 loss is :  10.875923\n",
      "iteration 702 loss is :  10.774171\n",
      "iteration 703 loss is :  10.863328\n",
      "iteration 704 loss is :  10.761448\n",
      "iteration 705 loss is :  10.850753\n",
      "iteration 706 loss is :  10.748754\n",
      "iteration 707 loss is :  10.838195\n",
      "iteration 708 loss is :  10.736082\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 709 loss is :  10.825663\n",
      "iteration 710 loss is :  10.723441\n",
      "iteration 711 loss is :  10.813154\n",
      "iteration 712 loss is :  10.710831\n",
      "iteration 713 loss is :  10.800636\n",
      "iteration 714 loss is :  10.698235\n",
      "iteration 715 loss is :  10.788153\n",
      "iteration 716 loss is :  10.685676\n",
      "iteration 717 loss is :  10.77569\n",
      "iteration 718 loss is :  10.673147\n",
      "iteration 719 loss is :  10.763274\n",
      "iteration 720 loss is :  10.660645\n",
      "iteration 721 loss is :  10.7508545\n",
      "iteration 722 loss is :  10.648172\n",
      "iteration 723 loss is :  10.738459\n",
      "iteration 724 loss is :  10.635724\n",
      "iteration 725 loss is :  10.726098\n",
      "iteration 726 loss is :  10.623308\n",
      "iteration 727 loss is :  10.713757\n",
      "iteration 728 loss is :  10.610916\n",
      "iteration 729 loss is :  10.701427\n",
      "iteration 730 loss is :  10.598539\n",
      "iteration 731 loss is :  10.689136\n",
      "iteration 732 loss is :  10.586207\n",
      "iteration 733 loss is :  10.676859\n",
      "iteration 734 loss is :  10.573913\n",
      "iteration 735 loss is :  10.66463\n",
      "iteration 736 loss is :  10.561638\n",
      "iteration 737 loss is :  10.65243\n",
      "iteration 738 loss is :  10.549396\n",
      "iteration 739 loss is :  10.640232\n",
      "iteration 740 loss is :  10.537186\n",
      "iteration 741 loss is :  10.628088\n",
      "iteration 742 loss is :  10.524994\n",
      "iteration 743 loss is :  10.615958\n",
      "iteration 744 loss is :  10.512845\n",
      "iteration 745 loss is :  10.603863\n",
      "iteration 746 loss is :  10.500727\n",
      "iteration 747 loss is :  10.591809\n",
      "iteration 748 loss is :  10.488632\n",
      "iteration 749 loss is :  10.579776\n",
      "iteration 750 loss is :  10.476573\n",
      "iteration 751 loss is :  10.567778\n",
      "iteration 752 loss is :  10.464552\n",
      "iteration 753 loss is :  10.5558195\n",
      "iteration 754 loss is :  10.452563\n",
      "iteration 755 loss is :  10.543895\n",
      "iteration 756 loss is :  10.440611\n",
      "iteration 757 loss is :  10.531983\n",
      "iteration 758 loss is :  10.428682\n",
      "iteration 759 loss is :  10.520124\n",
      "iteration 760 loss is :  10.416784\n",
      "iteration 761 loss is :  10.508284\n",
      "iteration 762 loss is :  10.404911\n",
      "iteration 763 loss is :  10.49648\n",
      "iteration 764 loss is :  10.393081\n",
      "iteration 765 loss is :  10.484727\n",
      "iteration 766 loss is :  10.381301\n",
      "iteration 767 loss is :  10.47301\n",
      "iteration 768 loss is :  10.369532\n",
      "iteration 769 loss is :  10.461311\n",
      "iteration 770 loss is :  10.357794\n",
      "iteration 771 loss is :  10.449659\n",
      "iteration 772 loss is :  10.3461075\n",
      "iteration 773 loss is :  10.438032\n",
      "iteration 774 loss is :  10.3344555\n",
      "iteration 775 loss is :  10.426464\n",
      "iteration 776 loss is :  10.322831\n",
      "iteration 777 loss is :  10.414913\n",
      "iteration 778 loss is :  10.31125\n",
      "iteration 779 loss is :  10.403415\n",
      "iteration 780 loss is :  10.299695\n",
      "iteration 781 loss is :  10.391939\n",
      "iteration 782 loss is :  10.288174\n",
      "iteration 783 loss is :  10.3805065\n",
      "iteration 784 loss is :  10.276701\n",
      "iteration 785 loss is :  10.369114\n",
      "iteration 786 loss is :  10.265249\n",
      "iteration 787 loss is :  10.357769\n",
      "iteration 788 loss is :  10.253847\n",
      "iteration 789 loss is :  10.34645\n",
      "iteration 790 loss is :  10.242464\n",
      "iteration 791 loss is :  10.33517\n",
      "iteration 792 loss is :  10.231131\n",
      "iteration 793 loss is :  10.32393\n",
      "iteration 794 loss is :  10.219833\n",
      "iteration 795 loss is :  10.312736\n",
      "iteration 796 loss is :  10.208574\n",
      "iteration 797 loss is :  10.301579\n",
      "iteration 798 loss is :  10.197353\n",
      "iteration 799 loss is :  10.29046\n",
      "iteration 800 loss is :  10.18616\n",
      "iteration 801 loss is :  10.279371\n",
      "iteration 802 loss is :  10.17501\n",
      "iteration 803 loss is :  10.268335\n",
      "iteration 804 loss is :  10.163893\n",
      "iteration 805 loss is :  10.257335\n",
      "iteration 806 loss is :  10.152828\n",
      "iteration 807 loss is :  10.246372\n",
      "iteration 808 loss is :  10.141803\n",
      "iteration 809 loss is :  10.235453\n",
      "iteration 810 loss is :  10.1307955\n",
      "iteration 811 loss is :  10.224575\n",
      "iteration 812 loss is :  10.11985\n",
      "iteration 813 loss is :  10.21373\n",
      "iteration 814 loss is :  10.108934\n",
      "iteration 815 loss is :  10.202943\n",
      "iteration 816 loss is :  10.098053\n",
      "iteration 817 loss is :  10.192184\n",
      "iteration 818 loss is :  10.087223\n",
      "iteration 819 loss is :  10.18148\n",
      "iteration 820 loss is :  10.076414\n",
      "iteration 821 loss is :  10.170789\n",
      "iteration 822 loss is :  10.065655\n",
      "iteration 823 loss is :  10.160161\n",
      "iteration 824 loss is :  10.0549345\n",
      "iteration 825 loss is :  10.149552\n",
      "iteration 826 loss is :  10.044259\n",
      "iteration 827 loss is :  10.139001\n",
      "iteration 828 loss is :  10.033613\n",
      "iteration 829 loss is :  10.12849\n",
      "iteration 830 loss is :  10.023026\n",
      "iteration 831 loss is :  10.118035\n",
      "iteration 832 loss is :  10.012474\n",
      "iteration 833 loss is :  10.1076\n",
      "iteration 834 loss is :  10.001957\n",
      "iteration 835 loss is :  10.097221\n",
      "iteration 836 loss is :  9.991474\n",
      "iteration 837 loss is :  10.086864\n",
      "iteration 838 loss is :  9.98104\n",
      "iteration 839 loss is :  10.076565\n",
      "iteration 840 loss is :  9.970637\n",
      "iteration 841 loss is :  10.066298\n",
      "iteration 842 loss is :  9.960277\n",
      "iteration 843 loss is :  10.056075\n",
      "iteration 844 loss is :  9.949957\n",
      "iteration 845 loss is :  10.045865\n",
      "iteration 846 loss is :  9.939674\n",
      "iteration 847 loss is :  10.035714\n",
      "iteration 848 loss is :  9.929434\n",
      "iteration 849 loss is :  10.025605\n",
      "iteration 850 loss is :  9.919233\n",
      "iteration 851 loss is :  10.015541\n",
      "iteration 852 loss is :  9.909072\n",
      "iteration 853 loss is :  10.005503\n",
      "iteration 854 loss is :  9.898948\n",
      "iteration 855 loss is :  9.99553\n",
      "iteration 856 loss is :  9.888858\n",
      "iteration 857 loss is :  9.9855585\n",
      "iteration 858 loss is :  9.878817\n",
      "iteration 859 loss is :  9.975641\n",
      "iteration 860 loss is :  9.8688\n",
      "iteration 861 loss is :  9.965754\n",
      "iteration 862 loss is :  9.858819\n",
      "iteration 863 loss is :  9.955901\n",
      "iteration 864 loss is :  9.848887\n",
      "iteration 865 loss is :  9.946114\n",
      "iteration 866 loss is :  9.838987\n",
      "iteration 867 loss is :  9.936344\n",
      "iteration 868 loss is :  9.829123\n",
      "iteration 869 loss is :  9.926607\n",
      "iteration 870 loss is :  9.819299\n",
      "iteration 871 loss is :  9.916919\n",
      "iteration 872 loss is :  9.809517\n",
      "iteration 873 loss is :  9.907265\n",
      "iteration 874 loss is :  9.799752\n",
      "iteration 875 loss is :  9.897627\n",
      "iteration 876 loss is :  9.790033\n",
      "iteration 877 loss is :  9.888038\n",
      "iteration 878 loss is :  9.78035\n",
      "iteration 879 loss is :  9.878496\n",
      "iteration 880 loss is :  9.770684\n",
      "iteration 881 loss is :  9.868951\n",
      "iteration 882 loss is :  9.76107\n",
      "iteration 883 loss is :  9.859459\n",
      "iteration 884 loss is :  9.75147\n",
      "iteration 885 loss is :  9.849985\n",
      "iteration 886 loss is :  9.741902\n",
      "iteration 887 loss is :  9.840535\n",
      "iteration 888 loss is :  9.732374\n",
      "iteration 889 loss is :  9.831132\n",
      "iteration 890 loss is :  9.722882\n",
      "iteration 891 loss is :  9.821764\n",
      "iteration 892 loss is :  9.713402\n",
      "iteration 893 loss is :  9.812415\n",
      "iteration 894 loss is :  9.703973\n",
      "iteration 895 loss is :  9.803095\n",
      "iteration 896 loss is :  9.694556\n",
      "iteration 897 loss is :  9.793798\n",
      "iteration 898 loss is :  9.685164\n",
      "iteration 899 loss is :  9.784525\n",
      "iteration 900 loss is :  9.675808\n",
      "iteration 901 loss is :  9.775279\n",
      "iteration 902 loss is :  9.666478\n",
      "iteration 903 loss is :  9.766037\n",
      "iteration 904 loss is :  9.657167\n",
      "iteration 905 loss is :  9.75684\n",
      "iteration 906 loss is :  9.6478815\n",
      "iteration 907 loss is :  9.747651\n",
      "iteration 908 loss is :  9.638621\n",
      "iteration 909 loss is :  9.738487\n",
      "iteration 910 loss is :  9.629375\n",
      "iteration 911 loss is :  9.729329\n",
      "iteration 912 loss is :  9.620158\n",
      "iteration 913 loss is :  9.720196\n",
      "iteration 914 loss is :  9.610967\n",
      "iteration 915 loss is :  9.711079\n",
      "iteration 916 loss is :  9.601781\n",
      "iteration 917 loss is :  9.701981\n",
      "iteration 918 loss is :  9.5926485\n",
      "iteration 919 loss is :  9.692914\n",
      "iteration 920 loss is :  9.58351\n",
      "iteration 921 loss is :  9.683863\n",
      "iteration 922 loss is :  9.574391\n",
      "iteration 923 loss is :  9.674804\n",
      "iteration 924 loss is :  9.5653\n",
      "iteration 925 loss is :  9.665767\n",
      "iteration 926 loss is :  9.55623\n",
      "iteration 927 loss is :  9.656757\n",
      "iteration 928 loss is :  9.547184\n",
      "iteration 929 loss is :  9.647781\n",
      "iteration 930 loss is :  9.538152\n",
      "iteration 931 loss is :  9.638785\n",
      "iteration 932 loss is :  9.529145\n",
      "iteration 933 loss is :  9.629817\n",
      "iteration 934 loss is :  9.520147\n",
      "iteration 935 loss is :  9.620867\n",
      "iteration 936 loss is :  9.511166\n",
      "iteration 937 loss is :  9.611918\n",
      "iteration 938 loss is :  9.502199\n",
      "iteration 939 loss is :  9.602985\n",
      "iteration 940 loss is :  9.493264\n",
      "iteration 941 loss is :  9.594079\n",
      "iteration 942 loss is :  9.48433\n",
      "iteration 943 loss is :  9.585188\n",
      "iteration 944 loss is :  9.475426\n",
      "iteration 945 loss is :  9.576286\n",
      "iteration 946 loss is :  9.466537\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 947 loss is :  9.567426\n",
      "iteration 948 loss is :  9.457667\n",
      "iteration 949 loss is :  9.558563\n",
      "iteration 950 loss is :  9.448823\n",
      "iteration 951 loss is :  9.549722\n",
      "iteration 952 loss is :  9.439986\n",
      "iteration 953 loss is :  9.540891\n",
      "iteration 954 loss is :  9.431157\n",
      "iteration 955 loss is :  9.532077\n",
      "iteration 956 loss is :  9.42236\n",
      "iteration 957 loss is :  9.52328\n",
      "iteration 958 loss is :  9.4135685\n",
      "iteration 959 loss is :  9.514481\n",
      "iteration 960 loss is :  9.40479\n",
      "iteration 961 loss is :  9.505697\n",
      "iteration 962 loss is :  9.396035\n",
      "iteration 963 loss is :  9.496924\n",
      "iteration 964 loss is :  9.387299\n",
      "iteration 965 loss is :  9.488179\n",
      "iteration 966 loss is :  9.378574\n",
      "iteration 967 loss is :  9.479438\n",
      "iteration 968 loss is :  9.369868\n",
      "iteration 969 loss is :  9.470711\n",
      "iteration 970 loss is :  9.361175\n",
      "iteration 971 loss is :  9.461995\n",
      "iteration 972 loss is :  9.352508\n",
      "iteration 973 loss is :  9.453308\n",
      "iteration 974 loss is :  9.343851\n",
      "iteration 975 loss is :  9.444625\n",
      "iteration 976 loss is :  9.335206\n",
      "iteration 977 loss is :  9.435939\n",
      "iteration 978 loss is :  9.326587\n",
      "iteration 979 loss is :  9.427288\n",
      "iteration 980 loss is :  9.317971\n",
      "iteration 981 loss is :  9.418633\n",
      "iteration 982 loss is :  9.309374\n",
      "iteration 983 loss is :  9.409999\n",
      "iteration 984 loss is :  9.300802\n",
      "iteration 985 loss is :  9.401386\n",
      "iteration 986 loss is :  9.292253\n",
      "iteration 987 loss is :  9.392783\n",
      "iteration 988 loss is :  9.283702\n",
      "iteration 989 loss is :  9.384182\n",
      "iteration 990 loss is :  9.275162\n",
      "iteration 991 loss is :  9.375598\n",
      "iteration 992 loss is :  9.266658\n",
      "iteration 993 loss is :  9.367053\n",
      "iteration 994 loss is :  9.258164\n",
      "iteration 995 loss is :  9.3585005\n",
      "iteration 996 loss is :  9.2496805\n",
      "iteration 997 loss is :  9.349965\n",
      "iteration 998 loss is :  9.241213\n",
      "iteration 999 loss is :  9.3414345\n",
      "iteration 1000 loss is :  9.232768\n",
      "iteration 1001 loss is :  9.33293\n",
      "iteration 1002 loss is :  9.224339\n",
      "iteration 1003 loss is :  9.324436\n",
      "iteration 1004 loss is :  9.215924\n",
      "iteration 1005 loss is :  9.315955\n",
      "iteration 1006 loss is :  9.207525\n",
      "iteration 1007 loss is :  9.307494\n",
      "iteration 1008 loss is :  9.199146\n",
      "iteration 1009 loss is :  9.299036\n",
      "iteration 1010 loss is :  9.190771\n",
      "iteration 1011 loss is :  9.29059\n",
      "iteration 1012 loss is :  9.182411\n",
      "iteration 1013 loss is :  9.282169\n",
      "iteration 1014 loss is :  9.174077\n",
      "iteration 1015 loss is :  9.273761\n",
      "iteration 1016 loss is :  9.165761\n",
      "iteration 1017 loss is :  9.2653475\n",
      "iteration 1018 loss is :  9.157451\n",
      "iteration 1019 loss is :  9.256967\n",
      "iteration 1020 loss is :  9.149169\n",
      "iteration 1021 loss is :  9.248601\n",
      "iteration 1022 loss is :  9.140902\n",
      "iteration 1023 loss is :  9.240258\n",
      "iteration 1024 loss is :  9.132648\n",
      "iteration 1025 loss is :  9.23192\n",
      "iteration 1026 loss is :  9.12441\n",
      "iteration 1027 loss is :  9.223594\n",
      "iteration 1028 loss is :  9.116179\n",
      "iteration 1029 loss is :  9.215277\n",
      "iteration 1030 loss is :  9.107987\n",
      "iteration 1031 loss is :  9.206993\n",
      "iteration 1032 loss is :  9.099796\n",
      "iteration 1033 loss is :  9.198725\n",
      "iteration 1034 loss is :  9.091623\n",
      "iteration 1035 loss is :  9.190463\n",
      "iteration 1036 loss is :  9.083457\n",
      "iteration 1037 loss is :  9.182205\n",
      "iteration 1038 loss is :  9.075312\n",
      "iteration 1039 loss is :  9.173966\n",
      "iteration 1040 loss is :  9.067186\n",
      "iteration 1041 loss is :  9.1657505\n",
      "iteration 1042 loss is :  9.059075\n",
      "iteration 1043 loss is :  9.157542\n",
      "iteration 1044 loss is :  9.050982\n",
      "iteration 1045 loss is :  9.149358\n",
      "iteration 1046 loss is :  9.042908\n",
      "iteration 1047 loss is :  9.141179\n",
      "iteration 1048 loss is :  9.034839\n",
      "iteration 1049 loss is :  9.133027\n",
      "iteration 1050 loss is :  9.026808\n",
      "iteration 1051 loss is :  9.124892\n",
      "iteration 1052 loss is :  9.018785\n",
      "iteration 1053 loss is :  9.11677\n",
      "iteration 1054 loss is :  9.010762\n",
      "iteration 1055 loss is :  9.108652\n",
      "iteration 1056 loss is :  9.002765\n",
      "iteration 1057 loss is :  9.100559\n",
      "iteration 1058 loss is :  8.994783\n",
      "iteration 1059 loss is :  9.092484\n",
      "iteration 1060 loss is :  8.986828\n",
      "iteration 1061 loss is :  9.084422\n",
      "iteration 1062 loss is :  8.978878\n",
      "iteration 1063 loss is :  9.076375\n",
      "iteration 1064 loss is :  8.970943\n",
      "iteration 1065 loss is :  9.068339\n",
      "iteration 1066 loss is :  8.963017\n",
      "iteration 1067 loss is :  9.060318\n",
      "iteration 1068 loss is :  8.95511\n",
      "iteration 1069 loss is :  9.052319\n",
      "iteration 1070 loss is :  8.947224\n",
      "iteration 1071 loss is :  9.04433\n",
      "iteration 1072 loss is :  8.93936\n",
      "iteration 1073 loss is :  9.0363655\n",
      "iteration 1074 loss is :  8.931513\n",
      "iteration 1075 loss is :  9.02842\n",
      "iteration 1076 loss is :  8.923672\n",
      "iteration 1077 loss is :  9.020486\n",
      "iteration 1078 loss is :  8.915852\n",
      "iteration 1079 loss is :  9.012566\n",
      "iteration 1080 loss is :  8.90804\n",
      "iteration 1081 loss is :  9.004665\n",
      "iteration 1082 loss is :  8.900245\n",
      "iteration 1083 loss is :  8.996769\n",
      "iteration 1084 loss is :  8.892468\n",
      "iteration 1085 loss is :  8.988901\n",
      "iteration 1086 loss is :  8.884709\n",
      "iteration 1087 loss is :  8.981046\n",
      "iteration 1088 loss is :  8.876961\n",
      "iteration 1089 loss is :  8.973203\n",
      "iteration 1090 loss is :  8.869229\n",
      "iteration 1091 loss is :  8.965378\n",
      "iteration 1092 loss is :  8.861501\n",
      "iteration 1093 loss is :  8.957554\n",
      "iteration 1094 loss is :  8.853802\n",
      "iteration 1095 loss is :  8.94977\n",
      "iteration 1096 loss is :  8.846114\n",
      "iteration 1097 loss is :  8.941982\n",
      "iteration 1098 loss is :  8.838439\n",
      "iteration 1099 loss is :  8.934218\n",
      "iteration 1100 loss is :  8.830781\n",
      "iteration 1101 loss is :  8.926466\n",
      "iteration 1102 loss is :  8.823134\n",
      "iteration 1103 loss is :  8.91873\n",
      "iteration 1104 loss is :  8.815519\n",
      "iteration 1105 loss is :  8.911013\n",
      "iteration 1106 loss is :  8.807906\n",
      "iteration 1107 loss is :  8.903309\n",
      "iteration 1108 loss is :  8.8003\n",
      "iteration 1109 loss is :  8.895619\n",
      "iteration 1110 loss is :  8.792708\n",
      "iteration 1111 loss is :  8.887955\n",
      "iteration 1112 loss is :  8.7851305\n",
      "iteration 1113 loss is :  8.88028\n",
      "iteration 1114 loss is :  8.777571\n",
      "iteration 1115 loss is :  8.87263\n",
      "iteration 1116 loss is :  8.770027\n",
      "iteration 1117 loss is :  8.865016\n",
      "iteration 1118 loss is :  8.762497\n",
      "iteration 1119 loss is :  8.857401\n",
      "iteration 1120 loss is :  8.754979\n",
      "iteration 1121 loss is :  8.849787\n",
      "iteration 1122 loss is :  8.747467\n",
      "iteration 1123 loss is :  8.842199\n",
      "iteration 1124 loss is :  8.739987\n",
      "iteration 1125 loss is :  8.834627\n",
      "iteration 1126 loss is :  8.732507\n",
      "iteration 1127 loss is :  8.827068\n",
      "iteration 1128 loss is :  8.725038\n",
      "iteration 1129 loss is :  8.819525\n",
      "iteration 1130 loss is :  8.717594\n",
      "iteration 1131 loss is :  8.811988\n",
      "iteration 1132 loss is :  8.710155\n",
      "iteration 1133 loss is :  8.804462\n",
      "iteration 1134 loss is :  8.702735\n",
      "iteration 1135 loss is :  8.796972\n",
      "iteration 1136 loss is :  8.695318\n",
      "iteration 1137 loss is :  8.789473\n",
      "iteration 1138 loss is :  8.687921\n",
      "iteration 1139 loss is :  8.782001\n",
      "iteration 1140 loss is :  8.680544\n",
      "iteration 1141 loss is :  8.774539\n",
      "iteration 1142 loss is :  8.673171\n",
      "iteration 1143 loss is :  8.767093\n",
      "iteration 1144 loss is :  8.665809\n",
      "iteration 1145 loss is :  8.759646\n",
      "iteration 1146 loss is :  8.658456\n",
      "iteration 1147 loss is :  8.752212\n",
      "iteration 1148 loss is :  8.651116\n",
      "iteration 1149 loss is :  8.744807\n",
      "iteration 1150 loss is :  8.643798\n",
      "iteration 1151 loss is :  8.737413\n",
      "iteration 1152 loss is :  8.636498\n",
      "iteration 1153 loss is :  8.730039\n",
      "iteration 1154 loss is :  8.6292\n",
      "iteration 1155 loss is :  8.722665\n",
      "iteration 1156 loss is :  8.621917\n",
      "iteration 1157 loss is :  8.715303\n",
      "iteration 1158 loss is :  8.614642\n",
      "iteration 1159 loss is :  8.707959\n",
      "iteration 1160 loss is :  8.607376\n",
      "iteration 1161 loss is :  8.700625\n",
      "iteration 1162 loss is :  8.600128\n",
      "iteration 1163 loss is :  8.693318\n",
      "iteration 1164 loss is :  8.592898\n",
      "iteration 1165 loss is :  8.685999\n",
      "iteration 1166 loss is :  8.585671\n",
      "iteration 1167 loss is :  8.678686\n",
      "iteration 1168 loss is :  8.578451\n",
      "iteration 1169 loss is :  8.671404\n",
      "iteration 1170 loss is :  8.57125\n",
      "iteration 1171 loss is :  8.664131\n",
      "iteration 1172 loss is :  8.564048\n",
      "iteration 1173 loss is :  8.656877\n",
      "iteration 1174 loss is :  8.556875\n",
      "iteration 1175 loss is :  8.649624\n",
      "iteration 1176 loss is :  8.549717\n",
      "iteration 1177 loss is :  8.642406\n",
      "iteration 1178 loss is :  8.542561\n",
      "iteration 1179 loss is :  8.635181\n",
      "iteration 1180 loss is :  8.535425\n",
      "iteration 1181 loss is :  8.627966\n",
      "iteration 1182 loss is :  8.528287\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 1183 loss is :  8.62077\n",
      "iteration 1184 loss is :  8.521154\n",
      "iteration 1185 loss is :  8.613577\n",
      "iteration 1186 loss is :  8.514048\n",
      "iteration 1187 loss is :  8.606395\n",
      "iteration 1188 loss is :  8.506949\n",
      "iteration 1189 loss is :  8.599227\n",
      "iteration 1190 loss is :  8.499858\n",
      "iteration 1191 loss is :  8.592072\n",
      "iteration 1192 loss is :  8.492775\n",
      "iteration 1193 loss is :  8.584917\n",
      "iteration 1194 loss is :  8.485719\n",
      "iteration 1195 loss is :  8.577797\n",
      "iteration 1196 loss is :  8.478667\n",
      "iteration 1197 loss is :  8.570688\n",
      "iteration 1198 loss is :  8.471618\n",
      "iteration 1199 loss is :  8.563575\n",
      "iteration 1200 loss is :  8.464594\n",
      "iteration 1201 loss is :  8.556475\n",
      "iteration 1202 loss is :  8.457562\n",
      "iteration 1203 loss is :  8.549389\n",
      "iteration 1204 loss is :  8.450556\n",
      "iteration 1205 loss is :  8.54231\n",
      "iteration 1206 loss is :  8.443547\n",
      "iteration 1207 loss is :  8.535235\n",
      "iteration 1208 loss is :  8.436561\n",
      "iteration 1209 loss is :  8.52818\n",
      "iteration 1210 loss is :  8.429579\n",
      "iteration 1211 loss is :  8.521136\n",
      "iteration 1212 loss is :  8.422602\n",
      "iteration 1213 loss is :  8.514107\n",
      "iteration 1214 loss is :  8.415655\n",
      "iteration 1215 loss is :  8.507091\n",
      "iteration 1216 loss is :  8.408706\n",
      "iteration 1217 loss is :  8.500071\n",
      "iteration 1218 loss is :  8.401772\n",
      "iteration 1219 loss is :  8.493072\n",
      "iteration 1220 loss is :  8.394841\n",
      "iteration 1221 loss is :  8.486086\n",
      "iteration 1222 loss is :  8.387927\n",
      "iteration 1223 loss is :  8.479101\n",
      "iteration 1224 loss is :  8.381022\n",
      "iteration 1225 loss is :  8.47214\n",
      "iteration 1226 loss is :  8.374131\n",
      "iteration 1227 loss is :  8.465176\n",
      "iteration 1228 loss is :  8.367241\n",
      "iteration 1229 loss is :  8.458236\n",
      "iteration 1230 loss is :  8.360371\n",
      "iteration 1231 loss is :  8.4513035\n",
      "iteration 1232 loss is :  8.353516\n",
      "iteration 1233 loss is :  8.444377\n",
      "iteration 1234 loss is :  8.3466625\n",
      "iteration 1235 loss is :  8.437451\n",
      "iteration 1236 loss is :  8.339804\n",
      "iteration 1237 loss is :  8.430534\n",
      "iteration 1238 loss is :  8.332976\n",
      "iteration 1239 loss is :  8.423651\n",
      "iteration 1240 loss is :  8.326148\n",
      "iteration 1241 loss is :  8.416757\n",
      "iteration 1242 loss is :  8.319344\n",
      "iteration 1243 loss is :  8.409895\n",
      "iteration 1244 loss is :  8.31254\n",
      "iteration 1245 loss is :  8.403025\n",
      "iteration 1246 loss is :  8.305748\n",
      "iteration 1247 loss is :  8.396161\n",
      "iteration 1248 loss is :  8.298956\n",
      "iteration 1249 loss is :  8.389303\n",
      "iteration 1250 loss is :  8.292179\n",
      "iteration 1251 loss is :  8.38247\n",
      "iteration 1252 loss is :  8.285422\n",
      "iteration 1253 loss is :  8.375654\n",
      "iteration 1254 loss is :  8.278672\n",
      "iteration 1255 loss is :  8.36884\n",
      "iteration 1256 loss is :  8.271936\n",
      "iteration 1257 loss is :  8.362028\n",
      "iteration 1258 loss is :  8.265193\n",
      "iteration 1259 loss is :  8.355231\n",
      "iteration 1260 loss is :  8.258475\n",
      "iteration 1261 loss is :  8.348446\n",
      "iteration 1262 loss is :  8.25176\n",
      "iteration 1263 loss is :  8.341672\n",
      "iteration 1264 loss is :  8.245061\n",
      "iteration 1265 loss is :  8.334923\n",
      "iteration 1266 loss is :  8.238369\n",
      "iteration 1267 loss is :  8.328156\n",
      "iteration 1268 loss is :  8.231686\n",
      "iteration 1269 loss is :  8.321412\n",
      "iteration 1270 loss is :  8.22501\n",
      "iteration 1271 loss is :  8.314668\n",
      "iteration 1272 loss is :  8.218347\n",
      "iteration 1273 loss is :  8.307941\n",
      "iteration 1274 loss is :  8.211672\n",
      "iteration 1275 loss is :  8.301217\n",
      "iteration 1276 loss is :  8.20503\n",
      "iteration 1277 loss is :  8.294514\n",
      "iteration 1278 loss is :  8.198395\n",
      "iteration 1279 loss is :  8.287812\n",
      "iteration 1280 loss is :  8.191779\n",
      "iteration 1281 loss is :  8.281139\n",
      "iteration 1282 loss is :  8.185159\n",
      "iteration 1283 loss is :  8.274462\n",
      "iteration 1284 loss is :  8.178549\n",
      "iteration 1285 loss is :  8.267794\n",
      "iteration 1286 loss is :  8.1719475\n",
      "iteration 1287 loss is :  8.261133\n",
      "iteration 1288 loss is :  8.165362\n",
      "iteration 1289 loss is :  8.254492\n",
      "iteration 1290 loss is :  8.158791\n",
      "iteration 1291 loss is :  8.247856\n",
      "iteration 1292 loss is :  8.1522255\n",
      "iteration 1293 loss is :  8.241243\n",
      "iteration 1294 loss is :  8.14567\n",
      "iteration 1295 loss is :  8.234619\n",
      "iteration 1296 loss is :  8.139114\n",
      "iteration 1297 loss is :  8.228013\n",
      "iteration 1298 loss is :  8.132568\n",
      "iteration 1299 loss is :  8.2214155\n",
      "iteration 1300 loss is :  8.12604\n",
      "iteration 1301 loss is :  8.214835\n",
      "iteration 1302 loss is :  8.119526\n",
      "iteration 1303 loss is :  8.208265\n",
      "iteration 1304 loss is :  8.113022\n",
      "iteration 1305 loss is :  8.201712\n",
      "iteration 1306 loss is :  8.10651\n",
      "iteration 1307 loss is :  8.19515\n",
      "iteration 1308 loss is :  8.100019\n",
      "iteration 1309 loss is :  8.18861\n",
      "iteration 1310 loss is :  8.093538\n",
      "iteration 1311 loss is :  8.182078\n",
      "iteration 1312 loss is :  8.087077\n",
      "iteration 1313 loss is :  8.175567\n",
      "iteration 1314 loss is :  8.080606\n",
      "iteration 1315 loss is :  8.169049\n",
      "iteration 1316 loss is :  8.07416\n",
      "iteration 1317 loss is :  8.1625595\n",
      "iteration 1318 loss is :  8.067716\n",
      "iteration 1319 loss is :  8.156073\n",
      "iteration 1320 loss is :  8.061284\n",
      "iteration 1321 loss is :  8.149607\n",
      "iteration 1322 loss is :  8.054863\n",
      "iteration 1323 loss is :  8.143144\n",
      "iteration 1324 loss is :  8.0484495\n",
      "iteration 1325 loss is :  8.136679\n",
      "iteration 1326 loss is :  8.042037\n",
      "iteration 1327 loss is :  8.130235\n",
      "iteration 1328 loss is :  8.035655\n",
      "iteration 1329 loss is :  8.123812\n",
      "iteration 1330 loss is :  8.029265\n",
      "iteration 1331 loss is :  8.117394\n",
      "iteration 1332 loss is :  8.022891\n",
      "iteration 1333 loss is :  8.110991\n",
      "iteration 1334 loss is :  8.016529\n",
      "iteration 1335 loss is :  8.104588\n",
      "iteration 1336 loss is :  8.010166\n",
      "iteration 1337 loss is :  8.098192\n",
      "iteration 1338 loss is :  8.003819\n",
      "iteration 1339 loss is :  8.091818\n",
      "iteration 1340 loss is :  7.9974785\n",
      "iteration 1341 loss is :  8.085448\n",
      "iteration 1342 loss is :  7.9911513\n",
      "iteration 1343 loss is :  8.079107\n",
      "iteration 1344 loss is :  7.984839\n",
      "iteration 1345 loss is :  8.072764\n",
      "iteration 1346 loss is :  7.9785337\n",
      "iteration 1347 loss is :  8.066438\n",
      "iteration 1348 loss is :  7.972224\n",
      "iteration 1349 loss is :  8.060114\n",
      "iteration 1350 loss is :  7.965939\n",
      "iteration 1351 loss is :  8.053806\n",
      "iteration 1352 loss is :  7.959654\n",
      "iteration 1353 loss is :  8.047504\n",
      "iteration 1354 loss is :  7.953386\n",
      "iteration 1355 loss is :  8.041218\n",
      "iteration 1356 loss is :  7.947126\n",
      "iteration 1357 loss is :  8.034955\n",
      "iteration 1358 loss is :  7.940884\n",
      "iteration 1359 loss is :  8.028696\n",
      "iteration 1360 loss is :  7.9346323\n",
      "iteration 1361 loss is :  8.02243\n",
      "iteration 1362 loss is :  7.9284086\n",
      "iteration 1363 loss is :  8.016189\n",
      "iteration 1364 loss is :  7.922182\n",
      "iteration 1365 loss is :  8.009957\n",
      "iteration 1366 loss is :  7.9159584\n",
      "iteration 1367 loss is :  8.003729\n",
      "iteration 1368 loss is :  7.9097505\n",
      "iteration 1369 loss is :  7.9975214\n",
      "iteration 1370 loss is :  7.9035497\n",
      "iteration 1371 loss is :  7.991321\n",
      "iteration 1372 loss is :  7.8973603\n",
      "iteration 1373 loss is :  7.9851284\n",
      "iteration 1374 loss is :  7.8911777\n",
      "iteration 1375 loss is :  7.978943\n",
      "iteration 1376 loss is :  7.885\n",
      "iteration 1377 loss is :  7.9727607\n",
      "iteration 1378 loss is :  7.8788376\n",
      "iteration 1379 loss is :  7.966601\n",
      "iteration 1380 loss is :  7.8726826\n",
      "iteration 1381 loss is :  7.960456\n",
      "iteration 1382 loss is :  7.866535\n",
      "iteration 1383 loss is :  7.954313\n",
      "iteration 1384 loss is :  7.8603897\n",
      "iteration 1385 loss is :  7.948173\n",
      "iteration 1386 loss is :  7.8542714\n",
      "iteration 1387 loss is :  7.942048\n",
      "iteration 1388 loss is :  7.84815\n",
      "iteration 1389 loss is :  7.9359465\n",
      "iteration 1390 loss is :  7.84204\n",
      "iteration 1391 loss is :  7.9298515\n",
      "iteration 1392 loss is :  7.835936\n",
      "iteration 1393 loss is :  7.923751\n",
      "iteration 1394 loss is :  7.829828\n",
      "iteration 1395 loss is :  7.917657\n",
      "iteration 1396 loss is :  7.823738\n",
      "iteration 1397 loss is :  7.911579\n",
      "iteration 1398 loss is :  7.817658\n",
      "iteration 1399 loss is :  7.9055157\n",
      "iteration 1400 loss is :  7.8115926\n",
      "iteration 1401 loss is :  7.899466\n",
      "iteration 1402 loss is :  7.805531\n",
      "iteration 1403 loss is :  7.8934274\n",
      "iteration 1404 loss is :  7.7994795\n",
      "iteration 1405 loss is :  7.8873916\n",
      "iteration 1406 loss is :  7.793434\n",
      "iteration 1407 loss is :  7.881354\n",
      "iteration 1408 loss is :  7.787381\n",
      "iteration 1409 loss is :  7.8753195\n",
      "iteration 1410 loss is :  7.7813535\n",
      "iteration 1411 loss is :  7.869308\n",
      "iteration 1412 loss is :  7.775337\n",
      "iteration 1413 loss is :  7.863314\n",
      "iteration 1414 loss is :  7.769312\n",
      "iteration 1415 loss is :  7.857319\n",
      "iteration 1416 loss is :  7.763304\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 1417 loss is :  7.851329\n",
      "iteration 1418 loss is :  7.757306\n",
      "iteration 1419 loss is :  7.8453593\n",
      "iteration 1420 loss is :  7.7513194\n",
      "iteration 1421 loss is :  7.839388\n",
      "iteration 1422 loss is :  7.745334\n",
      "iteration 1423 loss is :  7.8334336\n",
      "iteration 1424 loss is :  7.7393584\n",
      "iteration 1425 loss is :  7.827481\n",
      "iteration 1426 loss is :  7.733385\n",
      "iteration 1427 loss is :  7.8215322\n",
      "iteration 1428 loss is :  7.7274213\n",
      "iteration 1429 loss is :  7.8155937\n",
      "iteration 1430 loss is :  7.721474\n",
      "iteration 1431 loss is :  7.8096614\n",
      "iteration 1432 loss is :  7.7155204\n",
      "iteration 1433 loss is :  7.8037453\n",
      "iteration 1434 loss is :  7.7095823\n",
      "iteration 1435 loss is :  7.797843\n",
      "iteration 1436 loss is :  7.7036567\n",
      "iteration 1437 loss is :  7.7919354\n",
      "iteration 1438 loss is :  7.6977353\n",
      "iteration 1439 loss is :  7.7860475\n",
      "iteration 1440 loss is :  7.691824\n",
      "iteration 1441 loss is :  7.7801666\n",
      "iteration 1442 loss is :  7.6859193\n",
      "iteration 1443 loss is :  7.774279\n",
      "iteration 1444 loss is :  7.6800117\n",
      "iteration 1445 loss is :  7.7683983\n",
      "iteration 1446 loss is :  7.674114\n",
      "iteration 1447 loss is :  7.7625303\n",
      "iteration 1448 loss is :  7.6682324\n",
      "iteration 1449 loss is :  7.756678\n",
      "iteration 1450 loss is :  7.6623588\n",
      "iteration 1451 loss is :  7.750838\n",
      "iteration 1452 loss is :  7.656492\n",
      "iteration 1453 loss is :  7.745001\n",
      "iteration 1454 loss is :  7.6506305\n",
      "iteration 1455 loss is :  7.739182\n",
      "iteration 1456 loss is :  7.6447783\n",
      "iteration 1457 loss is :  7.7333603\n",
      "iteration 1458 loss is :  7.638933\n",
      "iteration 1459 loss is :  7.727539\n",
      "iteration 1460 loss is :  7.6330905\n",
      "iteration 1461 loss is :  7.7217283\n",
      "iteration 1462 loss is :  7.62726\n",
      "iteration 1463 loss is :  7.7159224\n",
      "iteration 1464 loss is :  7.621432\n",
      "iteration 1465 loss is :  7.710126\n",
      "iteration 1466 loss is :  7.615608\n",
      "iteration 1467 loss is :  7.704341\n",
      "iteration 1468 loss is :  7.609807\n",
      "iteration 1469 loss is :  7.6985683\n",
      "iteration 1470 loss is :  7.604006\n",
      "iteration 1471 loss is :  7.6928067\n",
      "iteration 1472 loss is :  7.598215\n",
      "iteration 1473 loss is :  7.68704\n",
      "iteration 1474 loss is :  7.592426\n",
      "iteration 1475 loss is :  7.6812844\n",
      "iteration 1476 loss is :  7.5866494\n",
      "iteration 1477 loss is :  7.6755466\n",
      "iteration 1478 loss is :  7.580878\n",
      "iteration 1479 loss is :  7.6697927\n",
      "iteration 1480 loss is :  7.57511\n",
      "iteration 1481 loss is :  7.6640544\n",
      "iteration 1482 loss is :  7.569349\n",
      "iteration 1483 loss is :  7.65833\n",
      "iteration 1484 loss is :  7.563599\n",
      "iteration 1485 loss is :  7.6526165\n",
      "iteration 1486 loss is :  7.5578523\n",
      "iteration 1487 loss is :  7.6468983\n",
      "iteration 1488 loss is :  7.5521207\n",
      "iteration 1489 loss is :  7.641197\n",
      "iteration 1490 loss is :  7.546398\n",
      "iteration 1491 loss is :  7.6355047\n",
      "iteration 1492 loss is :  7.5406775\n",
      "iteration 1493 loss is :  7.6298237\n",
      "iteration 1494 loss is :  7.534971\n",
      "iteration 1495 loss is :  7.6241407\n",
      "iteration 1496 loss is :  7.5292683\n",
      "iteration 1497 loss is :  7.6184764\n",
      "iteration 1498 loss is :  7.5235715\n",
      "iteration 1499 loss is :  7.6128016\n",
      "iteration 1500 loss is :  7.5178714\n",
      "iteration 1501 loss is :  7.607144\n",
      "iteration 1502 loss is :  7.5121922\n",
      "iteration 1503 loss is :  7.6014853\n",
      "iteration 1504 loss is :  7.506521\n",
      "iteration 1505 loss is :  7.5958514\n",
      "iteration 1506 loss is :  7.5008516\n",
      "iteration 1507 loss is :  7.590207\n",
      "iteration 1508 loss is :  7.495192\n",
      "iteration 1509 loss is :  7.5845857\n",
      "iteration 1510 loss is :  7.489545\n",
      "iteration 1511 loss is :  7.5789566\n",
      "iteration 1512 loss is :  7.483899\n",
      "iteration 1513 loss is :  7.573342\n",
      "iteration 1514 loss is :  7.4782667\n",
      "iteration 1515 loss is :  7.567744\n",
      "iteration 1516 loss is :  7.472638\n",
      "iteration 1517 loss is :  7.5621486\n",
      "iteration 1518 loss is :  7.4670143\n",
      "iteration 1519 loss is :  7.556553\n",
      "iteration 1520 loss is :  7.461399\n",
      "iteration 1521 loss is :  7.5509653\n",
      "iteration 1522 loss is :  7.4557924\n",
      "iteration 1523 loss is :  7.545385\n",
      "iteration 1524 loss is :  7.450201\n",
      "iteration 1525 loss is :  7.5398216\n",
      "iteration 1526 loss is :  7.4446044\n",
      "iteration 1527 loss is :  7.5342536\n",
      "iteration 1528 loss is :  7.4390187\n",
      "iteration 1529 loss is :  7.5287004\n",
      "iteration 1530 loss is :  7.433454\n",
      "iteration 1531 loss is :  7.523149\n",
      "iteration 1532 loss is :  7.4278812\n",
      "iteration 1533 loss is :  7.5176053\n",
      "iteration 1534 loss is :  7.422315\n",
      "iteration 1535 loss is :  7.5120792\n",
      "iteration 1536 loss is :  7.416769\n",
      "iteration 1537 loss is :  7.5065513\n",
      "iteration 1538 loss is :  7.411215\n",
      "iteration 1539 loss is :  7.5010266\n",
      "iteration 1540 loss is :  7.405684\n",
      "iteration 1541 loss is :  7.495511\n",
      "iteration 1542 loss is :  7.4001613\n",
      "iteration 1543 loss is :  7.4900126\n",
      "iteration 1544 loss is :  7.394631\n",
      "iteration 1545 loss is :  7.4845185\n",
      "iteration 1546 loss is :  7.3891215\n",
      "iteration 1547 loss is :  7.4790273\n",
      "iteration 1548 loss is :  7.3836145\n",
      "iteration 1549 loss is :  7.473546\n",
      "iteration 1550 loss is :  7.3781185\n",
      "iteration 1551 loss is :  7.46807\n",
      "iteration 1552 loss is :  7.3726244\n",
      "iteration 1553 loss is :  7.4626107\n",
      "iteration 1554 loss is :  7.3671412\n",
      "iteration 1555 loss is :  7.457142\n",
      "iteration 1556 loss is :  7.361665\n",
      "iteration 1557 loss is :  7.4516926\n",
      "iteration 1558 loss is :  7.356189\n",
      "iteration 1559 loss is :  7.4462485\n",
      "iteration 1560 loss is :  7.3507414\n",
      "iteration 1561 loss is :  7.440812\n",
      "iteration 1562 loss is :  7.3452816\n",
      "iteration 1563 loss is :  7.4353714\n",
      "iteration 1564 loss is :  7.3398414\n",
      "iteration 1565 loss is :  7.429958\n",
      "iteration 1566 loss is :  7.334407\n",
      "iteration 1567 loss is :  7.42454\n",
      "iteration 1568 loss is :  7.3289766\n",
      "iteration 1569 loss is :  7.419134\n",
      "iteration 1570 loss is :  7.3235545\n",
      "iteration 1571 loss is :  7.413742\n",
      "iteration 1572 loss is :  7.3181467\n",
      "iteration 1573 loss is :  7.4083443\n",
      "iteration 1574 loss is :  7.3127346\n",
      "iteration 1575 loss is :  7.40295\n",
      "iteration 1576 loss is :  7.307337\n",
      "iteration 1577 loss is :  7.397567\n",
      "iteration 1578 loss is :  7.3019524\n",
      "iteration 1579 loss is :  7.3922076\n",
      "iteration 1580 loss is :  7.2965775\n",
      "iteration 1581 loss is :  7.386847\n",
      "iteration 1582 loss is :  7.2912016\n",
      "iteration 1583 loss is :  7.3814898\n",
      "iteration 1584 loss is :  7.2858324\n",
      "iteration 1585 loss is :  7.3761377\n",
      "iteration 1586 loss is :  7.2804832\n",
      "iteration 1587 loss is :  7.370797\n",
      "iteration 1588 loss is :  7.2751274\n",
      "iteration 1589 loss is :  7.3654647\n",
      "iteration 1590 loss is :  7.2697825\n",
      "iteration 1591 loss is :  7.3601356\n",
      "iteration 1592 loss is :  7.264449\n",
      "iteration 1593 loss is :  7.354811\n",
      "iteration 1594 loss is :  7.2591214\n",
      "iteration 1595 loss is :  7.3495107\n",
      "iteration 1596 loss is :  7.253808\n",
      "iteration 1597 loss is :  7.3442082\n",
      "iteration 1598 loss is :  7.2485\n",
      "iteration 1599 loss is :  7.338912\n",
      "iteration 1600 loss is :  7.2431974\n",
      "iteration 1601 loss is :  7.333621\n",
      "iteration 1602 loss is :  7.237901\n",
      "iteration 1603 loss is :  7.328335\n",
      "iteration 1604 loss is :  7.2326117\n",
      "iteration 1605 loss is :  7.3230724\n",
      "iteration 1606 loss is :  7.2273383\n",
      "iteration 1607 loss is :  7.317802\n",
      "iteration 1608 loss is :  7.2220654\n",
      "iteration 1609 loss is :  7.312545\n",
      "iteration 1610 loss is :  7.2168026\n",
      "iteration 1611 loss is :  7.307293\n",
      "iteration 1612 loss is :  7.2115474\n",
      "iteration 1613 loss is :  7.302051\n",
      "iteration 1614 loss is :  7.2063017\n",
      "iteration 1615 loss is :  7.2968144\n",
      "iteration 1616 loss is :  7.2010593\n",
      "iteration 1617 loss is :  7.291588\n",
      "iteration 1618 loss is :  7.1958284\n",
      "iteration 1619 loss is :  7.2863617\n",
      "iteration 1620 loss is :  7.1906004\n",
      "iteration 1621 loss is :  7.281143\n",
      "iteration 1622 loss is :  7.1853905\n",
      "iteration 1623 loss is :  7.2759533\n",
      "iteration 1624 loss is :  7.1801796\n",
      "iteration 1625 loss is :  7.2707453\n",
      "iteration 1626 loss is :  7.1749816\n",
      "iteration 1627 loss is :  7.2655587\n",
      "iteration 1628 loss is :  7.1697927\n",
      "iteration 1629 loss is :  7.2603674\n",
      "iteration 1630 loss is :  7.1646056\n",
      "iteration 1631 loss is :  7.2551904\n",
      "iteration 1632 loss is :  7.159429\n",
      "iteration 1633 loss is :  7.250028\n",
      "iteration 1634 loss is :  7.15426\n",
      "iteration 1635 loss is :  7.244856\n",
      "iteration 1636 loss is :  7.149101\n",
      "iteration 1637 loss is :  7.2397084\n",
      "iteration 1638 loss is :  7.143937\n",
      "iteration 1639 loss is :  7.234551\n",
      "iteration 1640 loss is :  7.1387873\n",
      "iteration 1641 loss is :  7.2294183\n",
      "iteration 1642 loss is :  7.13366\n",
      "iteration 1643 loss is :  7.224289\n",
      "iteration 1644 loss is :  7.128531\n",
      "iteration 1645 loss is :  7.219156\n",
      "iteration 1646 loss is :  7.123404\n",
      "iteration 1647 loss is :  7.2140417\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 1648 loss is :  7.1182914\n",
      "iteration 1649 loss is :  7.208935\n",
      "iteration 1650 loss is :  7.113188\n",
      "iteration 1651 loss is :  7.203838\n",
      "iteration 1652 loss is :  7.108091\n",
      "iteration 1653 loss is :  7.1987486\n",
      "iteration 1654 loss is :  7.1030006\n",
      "iteration 1655 loss is :  7.193669\n",
      "iteration 1656 loss is :  7.097922\n",
      "iteration 1657 loss is :  7.188582\n",
      "iteration 1658 loss is :  7.092842\n",
      "iteration 1659 loss is :  7.1835003\n",
      "iteration 1660 loss is :  7.087772\n",
      "iteration 1661 loss is :  7.178438\n",
      "iteration 1662 loss is :  7.0827065\n",
      "iteration 1663 loss is :  7.1733723\n",
      "iteration 1664 loss is :  7.0776505\n",
      "iteration 1665 loss is :  7.1683245\n",
      "iteration 1666 loss is :  7.0726037\n",
      "iteration 1667 loss is :  7.163278\n",
      "iteration 1668 loss is :  7.067563\n",
      "iteration 1669 loss is :  7.1582446\n",
      "iteration 1670 loss is :  7.0625377\n",
      "iteration 1671 loss is :  7.1532245\n",
      "iteration 1672 loss is :  7.0575233\n",
      "iteration 1673 loss is :  7.148207\n",
      "iteration 1674 loss is :  7.0525103\n",
      "iteration 1675 loss is :  7.1431937\n",
      "iteration 1676 loss is :  7.047488\n",
      "iteration 1677 loss is :  7.138182\n",
      "iteration 1678 loss is :  7.0424905\n",
      "iteration 1679 loss is :  7.133176\n",
      "iteration 1680 loss is :  7.037496\n",
      "iteration 1681 loss is :  7.1281943\n",
      "iteration 1682 loss is :  7.0325103\n",
      "iteration 1683 loss is :  7.1232047\n",
      "iteration 1684 loss is :  7.027532\n",
      "iteration 1685 loss is :  7.118226\n",
      "iteration 1686 loss is :  7.0225573\n",
      "iteration 1687 loss is :  7.113246\n",
      "iteration 1688 loss is :  7.017594\n",
      "iteration 1689 loss is :  7.1082835\n",
      "iteration 1690 loss is :  7.0126348\n",
      "iteration 1691 loss is :  7.103329\n",
      "iteration 1692 loss is :  7.0076914\n",
      "iteration 1693 loss is :  7.0983834\n",
      "iteration 1694 loss is :  7.0027504\n",
      "iteration 1695 loss is :  7.0934424\n",
      "iteration 1696 loss is :  6.9978156\n",
      "iteration 1697 loss is :  7.0885077\n",
      "iteration 1698 loss is :  6.9928875\n",
      "iteration 1699 loss is :  7.0835795\n",
      "iteration 1700 loss is :  6.9879704\n",
      "iteration 1701 loss is :  7.078668\n",
      "iteration 1702 loss is :  6.9830604\n",
      "iteration 1703 loss is :  7.0737414\n",
      "iteration 1704 loss is :  6.978144\n",
      "iteration 1705 loss is :  7.0688243\n",
      "iteration 1706 loss is :  6.9732485\n",
      "iteration 1707 loss is :  7.06393\n",
      "iteration 1708 loss is :  6.9683547\n",
      "iteration 1709 loss is :  7.0590324\n",
      "iteration 1710 loss is :  6.9634604\n",
      "iteration 1711 loss is :  7.0541463\n",
      "iteration 1712 loss is :  6.958596\n",
      "iteration 1713 loss is :  7.0492682\n",
      "iteration 1714 loss is :  6.953723\n",
      "iteration 1715 loss is :  7.0444007\n",
      "iteration 1716 loss is :  6.948857\n",
      "iteration 1717 loss is :  7.03953\n",
      "iteration 1718 loss is :  6.9440045\n",
      "iteration 1719 loss is :  7.034678\n",
      "iteration 1720 loss is :  6.9391646\n",
      "iteration 1721 loss is :  7.0298247\n",
      "iteration 1722 loss is :  6.934308\n",
      "iteration 1723 loss is :  7.0249715\n",
      "iteration 1724 loss is :  6.929468\n",
      "iteration 1725 loss is :  7.02013\n",
      "iteration 1726 loss is :  6.92465\n",
      "iteration 1727 loss is :  7.0153093\n",
      "iteration 1728 loss is :  6.919821\n",
      "iteration 1729 loss is :  7.0104713\n",
      "iteration 1730 loss is :  6.915011\n",
      "iteration 1731 loss is :  7.005661\n",
      "iteration 1732 loss is :  6.9102097\n",
      "iteration 1733 loss is :  7.0008473\n",
      "iteration 1734 loss is :  6.9054003\n",
      "iteration 1735 loss is :  6.996045\n",
      "iteration 1736 loss is :  6.9006066\n",
      "iteration 1737 loss is :  6.991242\n",
      "iteration 1738 loss is :  6.895813\n",
      "iteration 1739 loss is :  6.986447\n",
      "iteration 1740 loss is :  6.891033\n",
      "iteration 1741 loss is :  6.981652\n",
      "iteration 1742 loss is :  6.8862605\n",
      "iteration 1743 loss is :  6.9768806\n",
      "iteration 1744 loss is :  6.8814955\n",
      "iteration 1745 loss is :  6.9721117\n",
      "iteration 1746 loss is :  6.8767357\n",
      "iteration 1747 loss is :  6.9673557\n",
      "iteration 1748 loss is :  6.871986\n",
      "iteration 1749 loss is :  6.9625854\n",
      "iteration 1750 loss is :  6.867236\n",
      "iteration 1751 loss is :  6.9578333\n",
      "iteration 1752 loss is :  6.862496\n",
      "iteration 1753 loss is :  6.9530773\n",
      "iteration 1754 loss is :  6.8577485\n",
      "iteration 1755 loss is :  6.948337\n",
      "iteration 1756 loss is :  6.853026\n",
      "iteration 1757 loss is :  6.943592\n",
      "iteration 1758 loss is :  6.848305\n",
      "iteration 1759 loss is :  6.9388824\n",
      "iteration 1760 loss is :  6.843591\n",
      "iteration 1761 loss is :  6.934156\n",
      "iteration 1762 loss is :  6.8388896\n",
      "iteration 1763 loss is :  6.92945\n",
      "iteration 1764 loss is :  6.8341827\n",
      "iteration 1765 loss is :  6.924741\n",
      "iteration 1766 loss is :  6.829489\n",
      "iteration 1767 loss is :  6.9200273\n",
      "iteration 1768 loss is :  6.8248005\n",
      "iteration 1769 loss is :  6.9153347\n",
      "iteration 1770 loss is :  6.8201203\n",
      "iteration 1771 loss is :  6.9106426\n",
      "iteration 1772 loss is :  6.815437\n",
      "iteration 1773 loss is :  6.90595\n",
      "iteration 1774 loss is :  6.8107667\n",
      "iteration 1775 loss is :  6.901278\n",
      "iteration 1776 loss is :  6.8061137\n",
      "iteration 1777 loss is :  6.8966174\n",
      "iteration 1778 loss is :  6.8014555\n",
      "iteration 1779 loss is :  6.891946\n",
      "iteration 1780 loss is :  6.796796\n",
      "iteration 1781 loss is :  6.8872766\n",
      "iteration 1782 loss is :  6.7921515\n",
      "iteration 1783 loss is :  6.8826194\n",
      "iteration 1784 loss is :  6.787509\n",
      "iteration 1785 loss is :  6.877968\n",
      "iteration 1786 loss is :  6.7828865\n",
      "iteration 1787 loss is :  6.873327\n",
      "iteration 1788 loss is :  6.778259\n",
      "iteration 1789 loss is :  6.8686957\n",
      "iteration 1790 loss is :  6.773637\n",
      "iteration 1791 loss is :  6.864068\n",
      "iteration 1792 loss is :  6.769029\n",
      "iteration 1793 loss is :  6.8594418\n",
      "iteration 1794 loss is :  6.764422\n",
      "iteration 1795 loss is :  6.85482\n",
      "iteration 1796 loss is :  6.7598214\n",
      "iteration 1797 loss is :  6.8502135\n",
      "iteration 1798 loss is :  6.755224\n",
      "iteration 1799 loss is :  6.845607\n",
      "iteration 1800 loss is :  6.7506385\n",
      "iteration 1801 loss is :  6.8410053\n",
      "iteration 1802 loss is :  6.746056\n",
      "iteration 1803 loss is :  6.836406\n",
      "iteration 1804 loss is :  6.741478\n",
      "iteration 1805 loss is :  6.8318152\n",
      "iteration 1806 loss is :  6.736907\n",
      "iteration 1807 loss is :  6.827241\n",
      "iteration 1808 loss is :  6.7323456\n",
      "iteration 1809 loss is :  6.8226666\n",
      "iteration 1810 loss is :  6.727788\n",
      "iteration 1811 loss is :  6.8180923\n",
      "iteration 1812 loss is :  6.723234\n",
      "iteration 1813 loss is :  6.813519\n",
      "iteration 1814 loss is :  6.718691\n",
      "iteration 1815 loss is :  6.8089643\n",
      "iteration 1816 loss is :  6.714147\n",
      "iteration 1817 loss is :  6.804412\n",
      "iteration 1818 loss is :  6.709618\n",
      "iteration 1819 loss is :  6.7998567\n",
      "iteration 1820 loss is :  6.7050805\n",
      "iteration 1821 loss is :  6.7953076\n",
      "iteration 1822 loss is :  6.700558\n",
      "iteration 1823 loss is :  6.79077\n",
      "iteration 1824 loss is :  6.6960473\n",
      "iteration 1825 loss is :  6.7862387\n",
      "iteration 1826 loss is :  6.6915345\n",
      "iteration 1827 loss is :  6.7817187\n",
      "iteration 1828 loss is :  6.687027\n",
      "iteration 1829 loss is :  6.777186\n",
      "iteration 1830 loss is :  6.6825237\n",
      "iteration 1831 loss is :  6.7726684\n",
      "iteration 1832 loss is :  6.6780367\n",
      "iteration 1833 loss is :  6.7681656\n",
      "iteration 1834 loss is :  6.6735497\n",
      "iteration 1835 loss is :  6.7636614\n",
      "iteration 1836 loss is :  6.6690693\n",
      "iteration 1837 loss is :  6.7591686\n",
      "iteration 1838 loss is :  6.664593\n",
      "iteration 1839 loss is :  6.754667\n",
      "iteration 1840 loss is :  6.6601195\n",
      "iteration 1841 loss is :  6.7501707\n",
      "iteration 1842 loss is :  6.6556654\n",
      "iteration 1843 loss is :  6.745707\n",
      "iteration 1844 loss is :  6.6512094\n",
      "iteration 1845 loss is :  6.741226\n",
      "iteration 1846 loss is :  6.6467447\n",
      "iteration 1847 loss is :  6.736747\n",
      "iteration 1848 loss is :  6.642297\n",
      "iteration 1849 loss is :  6.732283\n",
      "iteration 1850 loss is :  6.637852\n",
      "iteration 1851 loss is :  6.727812\n",
      "iteration 1852 loss is :  6.6334186\n",
      "iteration 1853 loss is :  6.7233596\n",
      "iteration 1854 loss is :  6.628986\n",
      "iteration 1855 loss is :  6.7189007\n",
      "iteration 1856 loss is :  6.62456\n",
      "iteration 1857 loss is :  6.714457\n",
      "iteration 1858 loss is :  6.620138\n",
      "iteration 1859 loss is :  6.710008\n",
      "iteration 1860 loss is :  6.615729\n",
      "iteration 1861 loss is :  6.705578\n",
      "iteration 1862 loss is :  6.61132\n",
      "iteration 1863 loss is :  6.701148\n",
      "iteration 1864 loss is :  6.606918\n",
      "iteration 1865 loss is :  6.6967278\n",
      "iteration 1866 loss is :  6.602525\n",
      "iteration 1867 loss is :  6.692314\n",
      "iteration 1868 loss is :  6.5981383\n",
      "iteration 1869 loss is :  6.6878963\n",
      "iteration 1870 loss is :  6.593751\n",
      "iteration 1871 loss is :  6.683493\n",
      "iteration 1872 loss is :  6.589364\n",
      "iteration 1873 loss is :  6.679071\n",
      "iteration 1874 loss is :  6.5849853\n",
      "iteration 1875 loss is :  6.67467\n",
      "iteration 1876 loss is :  6.580616\n",
      "iteration 1877 loss is :  6.670276\n",
      "iteration 1878 loss is :  6.5762625\n",
      "iteration 1879 loss is :  6.665905\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 1880 loss is :  6.5719013\n",
      "iteration 1881 loss is :  6.6615252\n",
      "iteration 1882 loss is :  6.5675445\n",
      "iteration 1883 loss is :  6.6571383\n",
      "iteration 1884 loss is :  6.5632014\n",
      "iteration 1885 loss is :  6.652765\n",
      "iteration 1886 loss is :  6.5588584\n",
      "iteration 1887 loss is :  6.6483927\n",
      "iteration 1888 loss is :  6.554521\n",
      "iteration 1889 loss is :  6.644036\n",
      "iteration 1890 loss is :  6.5501876\n",
      "iteration 1891 loss is :  6.6396704\n",
      "iteration 1892 loss is :  6.5458646\n",
      "iteration 1893 loss is :  6.6353207\n",
      "iteration 1894 loss is :  6.5415416\n",
      "iteration 1895 loss is :  6.630975\n",
      "iteration 1896 loss is :  6.5372267\n",
      "iteration 1897 loss is :  6.6266313\n",
      "iteration 1898 loss is :  6.5329127\n",
      "iteration 1899 loss is :  6.6222944\n",
      "iteration 1900 loss is :  6.5286202\n",
      "iteration 1901 loss is :  6.6179633\n",
      "iteration 1902 loss is :  6.524312\n",
      "iteration 1903 loss is :  6.6136265\n",
      "iteration 1904 loss is :  6.5200157\n",
      "iteration 1905 loss is :  6.6092997\n",
      "iteration 1906 loss is :  6.515723\n",
      "iteration 1907 loss is :  6.6049867\n",
      "iteration 1908 loss is :  6.511443\n",
      "iteration 1909 loss is :  6.600678\n",
      "iteration 1910 loss is :  6.5071626\n",
      "iteration 1911 loss is :  6.5963626\n",
      "iteration 1912 loss is :  6.50289\n",
      "iteration 1913 loss is :  6.592053\n",
      "iteration 1914 loss is :  6.498626\n",
      "iteration 1915 loss is :  6.5877533\n",
      "iteration 1916 loss is :  6.494358\n",
      "iteration 1917 loss is :  6.583462\n",
      "iteration 1918 loss is :  6.490104\n",
      "iteration 1919 loss is :  6.5791693\n",
      "iteration 1920 loss is :  6.4858446\n",
      "iteration 1921 loss is :  6.5748906\n",
      "iteration 1922 loss is :  6.4816093\n",
      "iteration 1923 loss is :  6.5706124\n",
      "iteration 1924 loss is :  6.477366\n",
      "iteration 1925 loss is :  6.566344\n",
      "iteration 1926 loss is :  6.473125\n",
      "iteration 1927 loss is :  6.562076\n",
      "iteration 1928 loss is :  6.468896\n",
      "iteration 1929 loss is :  6.557813\n",
      "iteration 1930 loss is :  6.4646654\n",
      "iteration 1931 loss is :  6.5535436\n",
      "iteration 1932 loss is :  6.460439\n",
      "iteration 1933 loss is :  6.5492835\n",
      "iteration 1934 loss is :  6.456225\n",
      "iteration 1935 loss is :  6.5450397\n",
      "iteration 1936 loss is :  6.452015\n",
      "iteration 1937 loss is :  6.5407968\n",
      "iteration 1938 loss is :  6.4478135\n",
      "iteration 1939 loss is :  6.5365644\n",
      "iteration 1940 loss is :  6.4436183\n",
      "iteration 1941 loss is :  6.5323267\n",
      "iteration 1942 loss is :  6.43942\n",
      "iteration 1943 loss is :  6.5280886\n",
      "iteration 1944 loss is :  6.435223\n",
      "iteration 1945 loss is :  6.5238543\n",
      "iteration 1946 loss is :  6.4310365\n",
      "iteration 1947 loss is :  6.5196333\n",
      "iteration 1948 loss is :  6.426852\n",
      "iteration 1949 loss is :  6.5154223\n",
      "iteration 1950 loss is :  6.4226832\n",
      "iteration 1951 loss is :  6.5112147\n",
      "iteration 1952 loss is :  6.4185176\n",
      "iteration 1953 loss is :  6.507012\n",
      "iteration 1954 loss is :  6.414347\n",
      "iteration 1955 loss is :  6.502806\n",
      "iteration 1956 loss is :  6.4101863\n",
      "iteration 1957 loss is :  6.498609\n",
      "iteration 1958 loss is :  6.4060335\n",
      "iteration 1959 loss is :  6.4944224\n",
      "iteration 1960 loss is :  6.401886\n",
      "iteration 1961 loss is :  6.490227\n",
      "iteration 1962 loss is :  6.397741\n",
      "iteration 1963 loss is :  6.4860477\n",
      "iteration 1964 loss is :  6.393601\n",
      "iteration 1965 loss is :  6.481871\n",
      "iteration 1966 loss is :  6.3894653\n",
      "iteration 1967 loss is :  6.477697\n",
      "iteration 1968 loss is :  6.3853335\n",
      "iteration 1969 loss is :  6.473519\n",
      "iteration 1970 loss is :  6.3812056\n",
      "iteration 1971 loss is :  6.469362\n",
      "iteration 1972 loss is :  6.377089\n",
      "iteration 1973 loss is :  6.465203\n",
      "iteration 1974 loss is :  6.3729773\n",
      "iteration 1975 loss is :  6.461053\n",
      "iteration 1976 loss is :  6.3688664\n",
      "iteration 1977 loss is :  6.456897\n",
      "iteration 1978 loss is :  6.3647585\n",
      "iteration 1979 loss is :  6.4527535\n",
      "iteration 1980 loss is :  6.3606586\n",
      "iteration 1981 loss is :  6.4486136\n",
      "iteration 1982 loss is :  6.356568\n",
      "iteration 1983 loss is :  6.444483\n",
      "iteration 1984 loss is :  6.352466\n",
      "iteration 1985 loss is :  6.4403486\n",
      "iteration 1986 loss is :  6.3483844\n",
      "iteration 1987 loss is :  6.4362216\n",
      "iteration 1988 loss is :  6.344306\n",
      "iteration 1989 loss is :  6.4320993\n",
      "iteration 1990 loss is :  6.3402305\n",
      "iteration 1991 loss is :  6.4279866\n",
      "iteration 1992 loss is :  6.336161\n",
      "iteration 1993 loss is :  6.4238763\n",
      "iteration 1994 loss is :  6.332096\n",
      "iteration 1995 loss is :  6.4197674\n",
      "iteration 1996 loss is :  6.32803\n",
      "iteration 1997 loss is :  6.415664\n",
      "iteration 1998 loss is :  6.3239837\n",
      "iteration 1999 loss is :  6.41157\n"
     ]
    }
   ],
   "source": [
    "sess = tf.Session()\n",
    "init = tf.global_variables_initializer()\n",
    "sess.run(init) \n",
    "\n",
    "iteration = 2000\n",
    "for i in range(iteration):\n",
    "    # input is X_train which is one hot encoded word\n",
    "    # label is Y_train which is one hot encoded neighbor word\n",
    "    sess.run(train_op, feed_dict={x: X_train, y_label: Y_train})\n",
    "    if i % 1 == 0:\n",
    "        print('iteration '+str(i)+' loss is : ', sess.run(loss, feed_dict={x: X_train, y_label: Y_train}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.89733064  1.0383393   1.1688597  ...  1.0693254   1.8568859\n",
      "   1.8416849 ]\n",
      " [-0.07568914  0.664055    0.06989011 ...  0.51823044  0.9393954\n",
      "   1.8250397 ]\n",
      " [ 0.48122534  1.7978618   0.638515   ...  0.50912267  1.1181664\n",
      "  -0.09690058]\n",
      " ...\n",
      " [ 0.58073765  1.283427    0.7367363  ...  0.6531396  -1.8552003\n",
      "   0.338383  ]\n",
      " [ 0.10226744  0.6122617   0.7714836  ...  0.68438077  2.1411216\n",
      "   2.161071  ]\n",
      " [-2.0029154   0.85830253  0.91746557 ...  0.5920444   1.2439437\n",
      "  -0.35756665]]\n"
     ]
    }
   ],
   "source": [
    "vectors = sess.run(W1 + b1)\n",
    "print(vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>word</th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "      <th>x4</th>\n",
       "      <th>x5</th>\n",
       "      <th>x6</th>\n",
       "      <th>x7</th>\n",
       "      <th>x8</th>\n",
       "      <th>x9</th>\n",
       "      <th>...</th>\n",
       "      <th>x91</th>\n",
       "      <th>x92</th>\n",
       "      <th>x93</th>\n",
       "      <th>x94</th>\n",
       "      <th>x95</th>\n",
       "      <th>x96</th>\n",
       "      <th>x97</th>\n",
       "      <th>x98</th>\n",
       "      <th>x99</th>\n",
       "      <th>x100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>147.32.84.21</td>\n",
       "      <td>-0.897331</td>\n",
       "      <td>1.038339</td>\n",
       "      <td>1.168860</td>\n",
       "      <td>0.548789</td>\n",
       "      <td>0.827424</td>\n",
       "      <td>1.350281</td>\n",
       "      <td>0.357317</td>\n",
       "      <td>0.151798</td>\n",
       "      <td>-1.203985</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.574610</td>\n",
       "      <td>-0.374309</td>\n",
       "      <td>-1.090475</td>\n",
       "      <td>-0.190525</td>\n",
       "      <td>2.256838</td>\n",
       "      <td>-0.995346</td>\n",
       "      <td>0.318381</td>\n",
       "      <td>1.069325</td>\n",
       "      <td>1.856886</td>\n",
       "      <td>1.841685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2759</td>\n",
       "      <td>-0.075689</td>\n",
       "      <td>0.664055</td>\n",
       "      <td>0.069890</td>\n",
       "      <td>0.113492</td>\n",
       "      <td>2.075718</td>\n",
       "      <td>1.165797</td>\n",
       "      <td>0.159236</td>\n",
       "      <td>0.656618</td>\n",
       "      <td>0.875231</td>\n",
       "      <td>...</td>\n",
       "      <td>1.370241</td>\n",
       "      <td>-0.426580</td>\n",
       "      <td>-1.050216</td>\n",
       "      <td>-0.632900</td>\n",
       "      <td>-0.132972</td>\n",
       "      <td>1.833304</td>\n",
       "      <td>-0.565339</td>\n",
       "      <td>0.518230</td>\n",
       "      <td>0.939395</td>\n",
       "      <td>1.825040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>203.125.50.50</td>\n",
       "      <td>0.481225</td>\n",
       "      <td>1.797862</td>\n",
       "      <td>0.638515</td>\n",
       "      <td>2.243348</td>\n",
       "      <td>2.395608</td>\n",
       "      <td>-0.890352</td>\n",
       "      <td>2.302247</td>\n",
       "      <td>1.510286</td>\n",
       "      <td>0.544332</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.913163</td>\n",
       "      <td>0.649294</td>\n",
       "      <td>0.177525</td>\n",
       "      <td>1.998903</td>\n",
       "      <td>1.194582</td>\n",
       "      <td>1.538517</td>\n",
       "      <td>0.798135</td>\n",
       "      <td>0.509123</td>\n",
       "      <td>1.118166</td>\n",
       "      <td>-0.096901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>46.158.48.2</td>\n",
       "      <td>1.809672</td>\n",
       "      <td>1.160131</td>\n",
       "      <td>1.087142</td>\n",
       "      <td>2.002876</td>\n",
       "      <td>-0.088767</td>\n",
       "      <td>1.478506</td>\n",
       "      <td>0.157406</td>\n",
       "      <td>0.930297</td>\n",
       "      <td>1.370391</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.043075</td>\n",
       "      <td>1.327622</td>\n",
       "      <td>2.011404</td>\n",
       "      <td>-0.581754</td>\n",
       "      <td>0.221714</td>\n",
       "      <td>2.069015</td>\n",
       "      <td>-0.875224</td>\n",
       "      <td>0.027485</td>\n",
       "      <td>0.830814</td>\n",
       "      <td>1.676701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>74.125.232.214</td>\n",
       "      <td>1.315566</td>\n",
       "      <td>1.503721</td>\n",
       "      <td>2.319758</td>\n",
       "      <td>-1.417383</td>\n",
       "      <td>1.881753</td>\n",
       "      <td>2.782334</td>\n",
       "      <td>0.656875</td>\n",
       "      <td>2.596758</td>\n",
       "      <td>-1.372827</td>\n",
       "      <td>...</td>\n",
       "      <td>0.614940</td>\n",
       "      <td>2.182342</td>\n",
       "      <td>2.397736</td>\n",
       "      <td>2.521049</td>\n",
       "      <td>1.555292</td>\n",
       "      <td>-0.858441</td>\n",
       "      <td>1.286282</td>\n",
       "      <td>1.166821</td>\n",
       "      <td>2.559523</td>\n",
       "      <td>0.647945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>76.13.114.90</td>\n",
       "      <td>0.884432</td>\n",
       "      <td>1.402307</td>\n",
       "      <td>0.236475</td>\n",
       "      <td>2.755326</td>\n",
       "      <td>0.007849</td>\n",
       "      <td>0.771038</td>\n",
       "      <td>1.154081</td>\n",
       "      <td>0.976132</td>\n",
       "      <td>-0.735547</td>\n",
       "      <td>...</td>\n",
       "      <td>1.582394</td>\n",
       "      <td>0.975448</td>\n",
       "      <td>-0.361619</td>\n",
       "      <td>1.121443</td>\n",
       "      <td>0.167561</td>\n",
       "      <td>-0.635591</td>\n",
       "      <td>2.206366</td>\n",
       "      <td>-1.205090</td>\n",
       "      <td>1.419789</td>\n",
       "      <td>0.983787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>51572</td>\n",
       "      <td>0.514282</td>\n",
       "      <td>0.252563</td>\n",
       "      <td>0.499660</td>\n",
       "      <td>-1.839670</td>\n",
       "      <td>0.198935</td>\n",
       "      <td>0.511351</td>\n",
       "      <td>-0.475192</td>\n",
       "      <td>0.597154</td>\n",
       "      <td>0.617414</td>\n",
       "      <td>...</td>\n",
       "      <td>1.126984</td>\n",
       "      <td>-0.027641</td>\n",
       "      <td>-0.332207</td>\n",
       "      <td>-0.307638</td>\n",
       "      <td>-0.472292</td>\n",
       "      <td>1.690702</td>\n",
       "      <td>0.915639</td>\n",
       "      <td>1.314826</td>\n",
       "      <td>0.630894</td>\n",
       "      <td>0.845138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>86.161.84.198</td>\n",
       "      <td>1.797912</td>\n",
       "      <td>0.926325</td>\n",
       "      <td>0.284184</td>\n",
       "      <td>0.353122</td>\n",
       "      <td>-1.392520</td>\n",
       "      <td>0.440905</td>\n",
       "      <td>-0.164116</td>\n",
       "      <td>0.122449</td>\n",
       "      <td>0.317926</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.295164</td>\n",
       "      <td>3.241334</td>\n",
       "      <td>0.917003</td>\n",
       "      <td>1.322532</td>\n",
       "      <td>0.547080</td>\n",
       "      <td>2.294626</td>\n",
       "      <td>1.474384</td>\n",
       "      <td>3.063208</td>\n",
       "      <td>-0.506767</td>\n",
       "      <td>0.645493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>178.4.36.49</td>\n",
       "      <td>0.069732</td>\n",
       "      <td>0.804143</td>\n",
       "      <td>-0.327944</td>\n",
       "      <td>3.628991</td>\n",
       "      <td>0.595381</td>\n",
       "      <td>0.449587</td>\n",
       "      <td>1.073174</td>\n",
       "      <td>1.300431</td>\n",
       "      <td>0.638524</td>\n",
       "      <td>...</td>\n",
       "      <td>0.760437</td>\n",
       "      <td>1.112388</td>\n",
       "      <td>0.236854</td>\n",
       "      <td>0.439323</td>\n",
       "      <td>-0.180617</td>\n",
       "      <td>1.338692</td>\n",
       "      <td>-0.215818</td>\n",
       "      <td>0.643084</td>\n",
       "      <td>-0.074870</td>\n",
       "      <td>0.236419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>52316</td>\n",
       "      <td>1.228511</td>\n",
       "      <td>0.638138</td>\n",
       "      <td>1.316916</td>\n",
       "      <td>0.701257</td>\n",
       "      <td>-0.010153</td>\n",
       "      <td>1.492005</td>\n",
       "      <td>0.559310</td>\n",
       "      <td>-0.244314</td>\n",
       "      <td>0.325908</td>\n",
       "      <td>...</td>\n",
       "      <td>2.468081</td>\n",
       "      <td>0.408820</td>\n",
       "      <td>1.113907</td>\n",
       "      <td>-0.232438</td>\n",
       "      <td>0.813623</td>\n",
       "      <td>0.449509</td>\n",
       "      <td>-0.330448</td>\n",
       "      <td>0.034572</td>\n",
       "      <td>0.109383</td>\n",
       "      <td>2.235850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>58.8.226.198</td>\n",
       "      <td>1.281058</td>\n",
       "      <td>-0.048206</td>\n",
       "      <td>-0.118079</td>\n",
       "      <td>0.842407</td>\n",
       "      <td>0.978136</td>\n",
       "      <td>-1.057679</td>\n",
       "      <td>1.108354</td>\n",
       "      <td>1.601815</td>\n",
       "      <td>0.421898</td>\n",
       "      <td>...</td>\n",
       "      <td>0.882990</td>\n",
       "      <td>0.797763</td>\n",
       "      <td>0.473813</td>\n",
       "      <td>0.640113</td>\n",
       "      <td>0.718233</td>\n",
       "      <td>0.106448</td>\n",
       "      <td>1.319540</td>\n",
       "      <td>0.065148</td>\n",
       "      <td>-0.532863</td>\n",
       "      <td>1.689204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>51019</td>\n",
       "      <td>2.035955</td>\n",
       "      <td>0.742344</td>\n",
       "      <td>0.416864</td>\n",
       "      <td>0.279828</td>\n",
       "      <td>1.844127</td>\n",
       "      <td>1.160855</td>\n",
       "      <td>1.311611</td>\n",
       "      <td>1.634317</td>\n",
       "      <td>0.617606</td>\n",
       "      <td>...</td>\n",
       "      <td>2.243950</td>\n",
       "      <td>1.576250</td>\n",
       "      <td>1.415075</td>\n",
       "      <td>-0.635900</td>\n",
       "      <td>1.021015</td>\n",
       "      <td>1.229937</td>\n",
       "      <td>-0.416690</td>\n",
       "      <td>-1.454134</td>\n",
       "      <td>0.647077</td>\n",
       "      <td>-0.349333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5318</td>\n",
       "      <td>1.634803</td>\n",
       "      <td>0.479017</td>\n",
       "      <td>0.471255</td>\n",
       "      <td>-0.310757</td>\n",
       "      <td>1.138414</td>\n",
       "      <td>1.524524</td>\n",
       "      <td>0.897687</td>\n",
       "      <td>0.037149</td>\n",
       "      <td>1.442197</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.359259</td>\n",
       "      <td>-1.138771</td>\n",
       "      <td>0.989995</td>\n",
       "      <td>2.509193</td>\n",
       "      <td>-0.763102</td>\n",
       "      <td>0.929420</td>\n",
       "      <td>-0.336079</td>\n",
       "      <td>1.183128</td>\n",
       "      <td>0.309567</td>\n",
       "      <td>-0.632391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>31518</td>\n",
       "      <td>-0.840729</td>\n",
       "      <td>2.473368</td>\n",
       "      <td>1.024202</td>\n",
       "      <td>0.609309</td>\n",
       "      <td>0.256692</td>\n",
       "      <td>-1.922309</td>\n",
       "      <td>0.097915</td>\n",
       "      <td>0.800605</td>\n",
       "      <td>-1.120466</td>\n",
       "      <td>...</td>\n",
       "      <td>0.893394</td>\n",
       "      <td>0.391185</td>\n",
       "      <td>-1.375062</td>\n",
       "      <td>0.994655</td>\n",
       "      <td>1.439185</td>\n",
       "      <td>1.416438</td>\n",
       "      <td>0.755577</td>\n",
       "      <td>-0.317367</td>\n",
       "      <td>1.747638</td>\n",
       "      <td>-0.545176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>147.32.84.68</td>\n",
       "      <td>-0.492344</td>\n",
       "      <td>1.115174</td>\n",
       "      <td>1.055364</td>\n",
       "      <td>1.460472</td>\n",
       "      <td>-0.798470</td>\n",
       "      <td>0.730227</td>\n",
       "      <td>-0.163092</td>\n",
       "      <td>1.801228</td>\n",
       "      <td>-0.208467</td>\n",
       "      <td>...</td>\n",
       "      <td>2.950172</td>\n",
       "      <td>0.613158</td>\n",
       "      <td>0.819825</td>\n",
       "      <td>0.633704</td>\n",
       "      <td>-0.005961</td>\n",
       "      <td>1.537209</td>\n",
       "      <td>-0.623843</td>\n",
       "      <td>-0.683515</td>\n",
       "      <td>0.444648</td>\n",
       "      <td>1.768843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>69.204.160.28</td>\n",
       "      <td>0.700052</td>\n",
       "      <td>2.226423</td>\n",
       "      <td>0.624228</td>\n",
       "      <td>0.962537</td>\n",
       "      <td>2.419705</td>\n",
       "      <td>1.702399</td>\n",
       "      <td>2.758665</td>\n",
       "      <td>3.549597</td>\n",
       "      <td>0.303176</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.050712</td>\n",
       "      <td>0.357555</td>\n",
       "      <td>1.031685</td>\n",
       "      <td>0.900700</td>\n",
       "      <td>0.401323</td>\n",
       "      <td>1.497588</td>\n",
       "      <td>1.041961</td>\n",
       "      <td>-0.019976</td>\n",
       "      <td>0.229779</td>\n",
       "      <td>0.870451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>192.166.145.6</td>\n",
       "      <td>1.026075</td>\n",
       "      <td>-0.058727</td>\n",
       "      <td>-0.519893</td>\n",
       "      <td>-0.542104</td>\n",
       "      <td>2.260275</td>\n",
       "      <td>0.881187</td>\n",
       "      <td>0.720510</td>\n",
       "      <td>-0.660529</td>\n",
       "      <td>-1.195983</td>\n",
       "      <td>...</td>\n",
       "      <td>1.668018</td>\n",
       "      <td>-0.046117</td>\n",
       "      <td>1.940023</td>\n",
       "      <td>0.952853</td>\n",
       "      <td>1.809393</td>\n",
       "      <td>-1.978976</td>\n",
       "      <td>1.316869</td>\n",
       "      <td>2.241636</td>\n",
       "      <td>0.671727</td>\n",
       "      <td>0.641895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>13363</td>\n",
       "      <td>2.096406</td>\n",
       "      <td>0.705950</td>\n",
       "      <td>0.413979</td>\n",
       "      <td>0.763562</td>\n",
       "      <td>0.583909</td>\n",
       "      <td>0.168505</td>\n",
       "      <td>1.447062</td>\n",
       "      <td>-0.846526</td>\n",
       "      <td>1.660644</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.494039</td>\n",
       "      <td>-0.812372</td>\n",
       "      <td>-0.023997</td>\n",
       "      <td>1.410699</td>\n",
       "      <td>1.910866</td>\n",
       "      <td>0.246955</td>\n",
       "      <td>0.505665</td>\n",
       "      <td>0.780509</td>\n",
       "      <td>-0.183022</td>\n",
       "      <td>-0.368206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>67.160.121.194</td>\n",
       "      <td>-0.111775</td>\n",
       "      <td>0.087736</td>\n",
       "      <td>0.799324</td>\n",
       "      <td>-0.026580</td>\n",
       "      <td>0.446313</td>\n",
       "      <td>1.088098</td>\n",
       "      <td>1.565305</td>\n",
       "      <td>1.297442</td>\n",
       "      <td>1.692738</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.989083</td>\n",
       "      <td>-0.032097</td>\n",
       "      <td>1.096282</td>\n",
       "      <td>2.349863</td>\n",
       "      <td>1.262412</td>\n",
       "      <td>0.899494</td>\n",
       "      <td>0.114332</td>\n",
       "      <td>0.078487</td>\n",
       "      <td>-1.289155</td>\n",
       "      <td>1.302531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>95.149.168.251</td>\n",
       "      <td>0.794601</td>\n",
       "      <td>2.492112</td>\n",
       "      <td>3.919671</td>\n",
       "      <td>1.833806</td>\n",
       "      <td>-2.033913</td>\n",
       "      <td>-0.362740</td>\n",
       "      <td>1.396368</td>\n",
       "      <td>0.648457</td>\n",
       "      <td>1.919550</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.557867</td>\n",
       "      <td>0.666718</td>\n",
       "      <td>1.132561</td>\n",
       "      <td>0.795950</td>\n",
       "      <td>1.500481</td>\n",
       "      <td>0.349687</td>\n",
       "      <td>1.254174</td>\n",
       "      <td>-0.451241</td>\n",
       "      <td>-1.217628</td>\n",
       "      <td>0.548110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>94.198.111.82</td>\n",
       "      <td>1.096221</td>\n",
       "      <td>0.328939</td>\n",
       "      <td>0.950791</td>\n",
       "      <td>-0.164715</td>\n",
       "      <td>1.637892</td>\n",
       "      <td>-0.043121</td>\n",
       "      <td>1.054474</td>\n",
       "      <td>0.211266</td>\n",
       "      <td>0.950749</td>\n",
       "      <td>...</td>\n",
       "      <td>1.012828</td>\n",
       "      <td>-0.152538</td>\n",
       "      <td>1.234861</td>\n",
       "      <td>-0.281867</td>\n",
       "      <td>1.400402</td>\n",
       "      <td>1.061536</td>\n",
       "      <td>-0.710520</td>\n",
       "      <td>0.075572</td>\n",
       "      <td>2.412917</td>\n",
       "      <td>1.420767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>147.32.84.165</td>\n",
       "      <td>-0.309435</td>\n",
       "      <td>-0.083729</td>\n",
       "      <td>1.227499</td>\n",
       "      <td>0.647278</td>\n",
       "      <td>2.346717</td>\n",
       "      <td>2.903686</td>\n",
       "      <td>0.198202</td>\n",
       "      <td>0.852055</td>\n",
       "      <td>0.316594</td>\n",
       "      <td>...</td>\n",
       "      <td>0.909025</td>\n",
       "      <td>0.682161</td>\n",
       "      <td>-1.031873</td>\n",
       "      <td>-0.016099</td>\n",
       "      <td>0.923578</td>\n",
       "      <td>1.791329</td>\n",
       "      <td>0.823432</td>\n",
       "      <td>0.490277</td>\n",
       "      <td>2.273566</td>\n",
       "      <td>-0.346761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>95.227.158.77</td>\n",
       "      <td>-0.711570</td>\n",
       "      <td>-1.102459</td>\n",
       "      <td>1.273976</td>\n",
       "      <td>-0.570579</td>\n",
       "      <td>0.671618</td>\n",
       "      <td>0.664352</td>\n",
       "      <td>0.108834</td>\n",
       "      <td>-0.234763</td>\n",
       "      <td>-1.795768</td>\n",
       "      <td>...</td>\n",
       "      <td>0.127483</td>\n",
       "      <td>0.221906</td>\n",
       "      <td>1.853326</td>\n",
       "      <td>1.432049</td>\n",
       "      <td>1.936878</td>\n",
       "      <td>-0.544655</td>\n",
       "      <td>0.953155</td>\n",
       "      <td>-0.455121</td>\n",
       "      <td>2.038569</td>\n",
       "      <td>-0.114402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>4793</td>\n",
       "      <td>0.995035</td>\n",
       "      <td>0.507893</td>\n",
       "      <td>0.570114</td>\n",
       "      <td>1.245277</td>\n",
       "      <td>-0.398104</td>\n",
       "      <td>0.079663</td>\n",
       "      <td>-0.767815</td>\n",
       "      <td>1.476544</td>\n",
       "      <td>0.028334</td>\n",
       "      <td>...</td>\n",
       "      <td>1.096818</td>\n",
       "      <td>1.566755</td>\n",
       "      <td>0.881113</td>\n",
       "      <td>1.823620</td>\n",
       "      <td>1.657318</td>\n",
       "      <td>-0.278470</td>\n",
       "      <td>1.513502</td>\n",
       "      <td>1.536893</td>\n",
       "      <td>1.759382</td>\n",
       "      <td>1.254017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>6911</td>\n",
       "      <td>1.646036</td>\n",
       "      <td>1.222038</td>\n",
       "      <td>-1.086776</td>\n",
       "      <td>0.754388</td>\n",
       "      <td>0.252542</td>\n",
       "      <td>1.333300</td>\n",
       "      <td>2.129134</td>\n",
       "      <td>0.298845</td>\n",
       "      <td>0.608951</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.171739</td>\n",
       "      <td>1.331473</td>\n",
       "      <td>2.125358</td>\n",
       "      <td>0.300442</td>\n",
       "      <td>0.556368</td>\n",
       "      <td>1.604478</td>\n",
       "      <td>0.629327</td>\n",
       "      <td>1.609062</td>\n",
       "      <td>1.146542</td>\n",
       "      <td>1.643509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>88.160.241.60</td>\n",
       "      <td>-0.401752</td>\n",
       "      <td>1.393662</td>\n",
       "      <td>-0.264355</td>\n",
       "      <td>-1.247841</td>\n",
       "      <td>0.628896</td>\n",
       "      <td>1.218504</td>\n",
       "      <td>1.769800</td>\n",
       "      <td>2.143489</td>\n",
       "      <td>0.840108</td>\n",
       "      <td>...</td>\n",
       "      <td>0.785203</td>\n",
       "      <td>0.591842</td>\n",
       "      <td>0.147244</td>\n",
       "      <td>0.828669</td>\n",
       "      <td>1.243851</td>\n",
       "      <td>2.061680</td>\n",
       "      <td>-0.009819</td>\n",
       "      <td>1.077649</td>\n",
       "      <td>-0.328895</td>\n",
       "      <td>0.055718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>203.99.179.112</td>\n",
       "      <td>0.630424</td>\n",
       "      <td>-1.223904</td>\n",
       "      <td>-0.019807</td>\n",
       "      <td>0.645410</td>\n",
       "      <td>0.436549</td>\n",
       "      <td>1.846159</td>\n",
       "      <td>-0.381286</td>\n",
       "      <td>0.368831</td>\n",
       "      <td>1.227113</td>\n",
       "      <td>...</td>\n",
       "      <td>0.155704</td>\n",
       "      <td>0.151103</td>\n",
       "      <td>1.481954</td>\n",
       "      <td>0.531424</td>\n",
       "      <td>0.774768</td>\n",
       "      <td>-0.102970</td>\n",
       "      <td>-0.429105</td>\n",
       "      <td>0.615498</td>\n",
       "      <td>-0.214952</td>\n",
       "      <td>-0.679337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>88.193.88.76</td>\n",
       "      <td>-1.393651</td>\n",
       "      <td>0.012959</td>\n",
       "      <td>0.364322</td>\n",
       "      <td>0.485375</td>\n",
       "      <td>-0.398019</td>\n",
       "      <td>-0.495255</td>\n",
       "      <td>0.774709</td>\n",
       "      <td>1.462987</td>\n",
       "      <td>0.319939</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.217846</td>\n",
       "      <td>0.282672</td>\n",
       "      <td>-0.411379</td>\n",
       "      <td>0.561824</td>\n",
       "      <td>-0.723491</td>\n",
       "      <td>0.202327</td>\n",
       "      <td>-0.121119</td>\n",
       "      <td>-0.241870</td>\n",
       "      <td>0.082464</td>\n",
       "      <td>-1.972011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>8000</td>\n",
       "      <td>3.634563</td>\n",
       "      <td>0.281187</td>\n",
       "      <td>-0.160636</td>\n",
       "      <td>0.189392</td>\n",
       "      <td>1.893791</td>\n",
       "      <td>0.802488</td>\n",
       "      <td>-1.097765</td>\n",
       "      <td>1.989843</td>\n",
       "      <td>0.434401</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.827450</td>\n",
       "      <td>0.525488</td>\n",
       "      <td>0.845032</td>\n",
       "      <td>-0.298382</td>\n",
       "      <td>2.185773</td>\n",
       "      <td>1.281961</td>\n",
       "      <td>-0.537364</td>\n",
       "      <td>2.507885</td>\n",
       "      <td>0.404093</td>\n",
       "      <td>0.650131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>129.6.15.28</td>\n",
       "      <td>1.236948</td>\n",
       "      <td>0.742899</td>\n",
       "      <td>3.195211</td>\n",
       "      <td>1.673277</td>\n",
       "      <td>-0.593115</td>\n",
       "      <td>1.026407</td>\n",
       "      <td>0.772482</td>\n",
       "      <td>-0.812714</td>\n",
       "      <td>1.110485</td>\n",
       "      <td>...</td>\n",
       "      <td>0.953716</td>\n",
       "      <td>0.147812</td>\n",
       "      <td>0.996055</td>\n",
       "      <td>-0.381551</td>\n",
       "      <td>0.151098</td>\n",
       "      <td>0.663533</td>\n",
       "      <td>1.689116</td>\n",
       "      <td>2.134418</td>\n",
       "      <td>0.341748</td>\n",
       "      <td>0.281706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464</th>\n",
       "      <td>49341</td>\n",
       "      <td>-0.560395</td>\n",
       "      <td>1.384934</td>\n",
       "      <td>0.652766</td>\n",
       "      <td>0.067068</td>\n",
       "      <td>1.321013</td>\n",
       "      <td>-0.759749</td>\n",
       "      <td>-1.050181</td>\n",
       "      <td>-0.118862</td>\n",
       "      <td>0.214881</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.165074</td>\n",
       "      <td>0.912992</td>\n",
       "      <td>1.202617</td>\n",
       "      <td>1.434320</td>\n",
       "      <td>0.417483</td>\n",
       "      <td>0.237063</td>\n",
       "      <td>0.600661</td>\n",
       "      <td>0.059620</td>\n",
       "      <td>-1.329937</td>\n",
       "      <td>-0.668846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>465</th>\n",
       "      <td>147.32.85.5</td>\n",
       "      <td>0.631980</td>\n",
       "      <td>0.287335</td>\n",
       "      <td>-0.047633</td>\n",
       "      <td>1.396060</td>\n",
       "      <td>1.386269</td>\n",
       "      <td>0.940499</td>\n",
       "      <td>1.096772</td>\n",
       "      <td>0.769486</td>\n",
       "      <td>-0.621018</td>\n",
       "      <td>...</td>\n",
       "      <td>0.701355</td>\n",
       "      <td>0.325464</td>\n",
       "      <td>-0.164755</td>\n",
       "      <td>0.956906</td>\n",
       "      <td>1.612222</td>\n",
       "      <td>0.700450</td>\n",
       "      <td>0.880975</td>\n",
       "      <td>0.569095</td>\n",
       "      <td>0.289293</td>\n",
       "      <td>0.764740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>30657</td>\n",
       "      <td>-0.397917</td>\n",
       "      <td>1.507463</td>\n",
       "      <td>0.810642</td>\n",
       "      <td>1.227995</td>\n",
       "      <td>1.592374</td>\n",
       "      <td>0.620145</td>\n",
       "      <td>-1.290038</td>\n",
       "      <td>0.676622</td>\n",
       "      <td>0.222824</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.863809</td>\n",
       "      <td>1.855566</td>\n",
       "      <td>-0.973069</td>\n",
       "      <td>0.458452</td>\n",
       "      <td>-1.135749</td>\n",
       "      <td>1.257886</td>\n",
       "      <td>0.182025</td>\n",
       "      <td>0.826035</td>\n",
       "      <td>0.498840</td>\n",
       "      <td>0.790112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>467</th>\n",
       "      <td>77.37.194.251</td>\n",
       "      <td>0.306267</td>\n",
       "      <td>0.584805</td>\n",
       "      <td>1.602183</td>\n",
       "      <td>-0.188734</td>\n",
       "      <td>2.252532</td>\n",
       "      <td>1.230337</td>\n",
       "      <td>1.279994</td>\n",
       "      <td>1.540911</td>\n",
       "      <td>0.067135</td>\n",
       "      <td>...</td>\n",
       "      <td>0.463550</td>\n",
       "      <td>-0.847110</td>\n",
       "      <td>0.418904</td>\n",
       "      <td>1.269640</td>\n",
       "      <td>-0.350296</td>\n",
       "      <td>1.703498</td>\n",
       "      <td>0.696683</td>\n",
       "      <td>2.041790</td>\n",
       "      <td>1.265325</td>\n",
       "      <td>0.887201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <td>147.32.86.181</td>\n",
       "      <td>-0.093423</td>\n",
       "      <td>3.045312</td>\n",
       "      <td>0.627166</td>\n",
       "      <td>1.670614</td>\n",
       "      <td>1.362169</td>\n",
       "      <td>0.499756</td>\n",
       "      <td>-2.100547</td>\n",
       "      <td>0.650885</td>\n",
       "      <td>0.342686</td>\n",
       "      <td>...</td>\n",
       "      <td>1.760501</td>\n",
       "      <td>1.271749</td>\n",
       "      <td>1.833856</td>\n",
       "      <td>0.231285</td>\n",
       "      <td>2.110642</td>\n",
       "      <td>0.939919</td>\n",
       "      <td>1.369057</td>\n",
       "      <td>0.559837</td>\n",
       "      <td>1.538809</td>\n",
       "      <td>0.008279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>469</th>\n",
       "      <td>23018</td>\n",
       "      <td>-0.421325</td>\n",
       "      <td>0.289654</td>\n",
       "      <td>0.707819</td>\n",
       "      <td>1.335384</td>\n",
       "      <td>0.760092</td>\n",
       "      <td>0.886493</td>\n",
       "      <td>0.853310</td>\n",
       "      <td>1.703280</td>\n",
       "      <td>0.191816</td>\n",
       "      <td>...</td>\n",
       "      <td>0.517908</td>\n",
       "      <td>-0.090548</td>\n",
       "      <td>-0.141383</td>\n",
       "      <td>1.501319</td>\n",
       "      <td>2.250376</td>\n",
       "      <td>-0.146305</td>\n",
       "      <td>0.840294</td>\n",
       "      <td>0.477808</td>\n",
       "      <td>-0.133752</td>\n",
       "      <td>0.374254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>40565</td>\n",
       "      <td>0.464585</td>\n",
       "      <td>2.713660</td>\n",
       "      <td>0.958501</td>\n",
       "      <td>-1.153836</td>\n",
       "      <td>1.077187</td>\n",
       "      <td>-0.716174</td>\n",
       "      <td>0.189335</td>\n",
       "      <td>-0.997213</td>\n",
       "      <td>-0.346337</td>\n",
       "      <td>...</td>\n",
       "      <td>0.952650</td>\n",
       "      <td>1.040361</td>\n",
       "      <td>0.019764</td>\n",
       "      <td>0.850117</td>\n",
       "      <td>0.015107</td>\n",
       "      <td>2.429726</td>\n",
       "      <td>1.637238</td>\n",
       "      <td>0.068725</td>\n",
       "      <td>0.063951</td>\n",
       "      <td>1.211536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <td>2774</td>\n",
       "      <td>-1.380675</td>\n",
       "      <td>0.972148</td>\n",
       "      <td>0.884002</td>\n",
       "      <td>1.488662</td>\n",
       "      <td>1.555927</td>\n",
       "      <td>2.954420</td>\n",
       "      <td>1.037272</td>\n",
       "      <td>-1.002583</td>\n",
       "      <td>0.359337</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003577</td>\n",
       "      <td>0.072338</td>\n",
       "      <td>2.048658</td>\n",
       "      <td>0.518016</td>\n",
       "      <td>0.962703</td>\n",
       "      <td>0.231017</td>\n",
       "      <td>0.737300</td>\n",
       "      <td>-0.284791</td>\n",
       "      <td>0.463807</td>\n",
       "      <td>1.571767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>213.226.244.55</td>\n",
       "      <td>0.565508</td>\n",
       "      <td>0.329057</td>\n",
       "      <td>0.009766</td>\n",
       "      <td>0.727189</td>\n",
       "      <td>1.323340</td>\n",
       "      <td>1.877180</td>\n",
       "      <td>0.333364</td>\n",
       "      <td>1.087386</td>\n",
       "      <td>0.457730</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.036515</td>\n",
       "      <td>0.118572</td>\n",
       "      <td>0.518128</td>\n",
       "      <td>1.172096</td>\n",
       "      <td>0.486083</td>\n",
       "      <td>1.267681</td>\n",
       "      <td>-0.828938</td>\n",
       "      <td>0.566484</td>\n",
       "      <td>2.679336</td>\n",
       "      <td>-0.818379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>63.135.80.58</td>\n",
       "      <td>0.435012</td>\n",
       "      <td>1.702355</td>\n",
       "      <td>-0.503747</td>\n",
       "      <td>1.862051</td>\n",
       "      <td>1.102790</td>\n",
       "      <td>0.051772</td>\n",
       "      <td>2.722988</td>\n",
       "      <td>-1.114797</td>\n",
       "      <td>-0.447549</td>\n",
       "      <td>...</td>\n",
       "      <td>0.334260</td>\n",
       "      <td>0.809752</td>\n",
       "      <td>-0.682559</td>\n",
       "      <td>0.376691</td>\n",
       "      <td>0.972959</td>\n",
       "      <td>0.504591</td>\n",
       "      <td>1.597688</td>\n",
       "      <td>0.982895</td>\n",
       "      <td>-0.411875</td>\n",
       "      <td>-0.911888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>178.200.203.145</td>\n",
       "      <td>-0.339449</td>\n",
       "      <td>0.157356</td>\n",
       "      <td>-0.469916</td>\n",
       "      <td>-0.327818</td>\n",
       "      <td>0.426694</td>\n",
       "      <td>0.585979</td>\n",
       "      <td>0.592479</td>\n",
       "      <td>-1.341660</td>\n",
       "      <td>-0.088474</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036497</td>\n",
       "      <td>-1.378752</td>\n",
       "      <td>1.807538</td>\n",
       "      <td>-0.498600</td>\n",
       "      <td>0.745016</td>\n",
       "      <td>-1.530732</td>\n",
       "      <td>-0.189081</td>\n",
       "      <td>-0.605807</td>\n",
       "      <td>-2.014765</td>\n",
       "      <td>1.142302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>147.230.32.193</td>\n",
       "      <td>2.256637</td>\n",
       "      <td>-0.108752</td>\n",
       "      <td>1.839135</td>\n",
       "      <td>1.771634</td>\n",
       "      <td>1.101400</td>\n",
       "      <td>2.210413</td>\n",
       "      <td>0.671699</td>\n",
       "      <td>-0.045613</td>\n",
       "      <td>2.174083</td>\n",
       "      <td>...</td>\n",
       "      <td>0.166658</td>\n",
       "      <td>1.888095</td>\n",
       "      <td>-0.408383</td>\n",
       "      <td>1.317657</td>\n",
       "      <td>0.765628</td>\n",
       "      <td>-0.492492</td>\n",
       "      <td>1.923769</td>\n",
       "      <td>1.814411</td>\n",
       "      <td>-0.896296</td>\n",
       "      <td>0.219959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>82.39.2.249</td>\n",
       "      <td>0.677403</td>\n",
       "      <td>0.243544</td>\n",
       "      <td>0.091746</td>\n",
       "      <td>0.725390</td>\n",
       "      <td>0.350245</td>\n",
       "      <td>0.493425</td>\n",
       "      <td>0.560017</td>\n",
       "      <td>0.853640</td>\n",
       "      <td>0.018194</td>\n",
       "      <td>...</td>\n",
       "      <td>1.168239</td>\n",
       "      <td>-0.349057</td>\n",
       "      <td>-0.305170</td>\n",
       "      <td>0.235523</td>\n",
       "      <td>-0.565100</td>\n",
       "      <td>-0.036158</td>\n",
       "      <td>2.410828</td>\n",
       "      <td>2.043656</td>\n",
       "      <td>1.751138</td>\n",
       "      <td>1.910241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>147.32.84.184</td>\n",
       "      <td>-0.780081</td>\n",
       "      <td>1.613062</td>\n",
       "      <td>-0.544166</td>\n",
       "      <td>0.522955</td>\n",
       "      <td>-0.592126</td>\n",
       "      <td>1.947488</td>\n",
       "      <td>1.837972</td>\n",
       "      <td>0.325368</td>\n",
       "      <td>-0.343267</td>\n",
       "      <td>...</td>\n",
       "      <td>1.434790</td>\n",
       "      <td>-0.035994</td>\n",
       "      <td>0.187794</td>\n",
       "      <td>1.394603</td>\n",
       "      <td>2.655153</td>\n",
       "      <td>-0.064278</td>\n",
       "      <td>2.555540</td>\n",
       "      <td>-0.128795</td>\n",
       "      <td>-0.789245</td>\n",
       "      <td>1.949822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>147.32.96.45</td>\n",
       "      <td>1.760448</td>\n",
       "      <td>1.615042</td>\n",
       "      <td>1.492031</td>\n",
       "      <td>-0.370347</td>\n",
       "      <td>0.529419</td>\n",
       "      <td>1.685722</td>\n",
       "      <td>-0.543488</td>\n",
       "      <td>0.541772</td>\n",
       "      <td>0.231811</td>\n",
       "      <td>...</td>\n",
       "      <td>2.265574</td>\n",
       "      <td>1.610020</td>\n",
       "      <td>-0.460652</td>\n",
       "      <td>-0.662355</td>\n",
       "      <td>-0.394565</td>\n",
       "      <td>1.273404</td>\n",
       "      <td>0.347328</td>\n",
       "      <td>1.367844</td>\n",
       "      <td>1.141068</td>\n",
       "      <td>0.966821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>94.179.93.205</td>\n",
       "      <td>0.670075</td>\n",
       "      <td>0.312818</td>\n",
       "      <td>-1.269048</td>\n",
       "      <td>0.214690</td>\n",
       "      <td>0.379805</td>\n",
       "      <td>1.201938</td>\n",
       "      <td>-0.798355</td>\n",
       "      <td>0.816026</td>\n",
       "      <td>2.721569</td>\n",
       "      <td>...</td>\n",
       "      <td>1.502677</td>\n",
       "      <td>-0.418117</td>\n",
       "      <td>0.932822</td>\n",
       "      <td>1.010649</td>\n",
       "      <td>1.592667</td>\n",
       "      <td>0.024429</td>\n",
       "      <td>1.631352</td>\n",
       "      <td>0.036423</td>\n",
       "      <td>-0.029284</td>\n",
       "      <td>3.236291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>90.183.39.86</td>\n",
       "      <td>0.934499</td>\n",
       "      <td>-1.561029</td>\n",
       "      <td>0.493987</td>\n",
       "      <td>0.009653</td>\n",
       "      <td>1.628919</td>\n",
       "      <td>-0.732768</td>\n",
       "      <td>1.595065</td>\n",
       "      <td>1.262217</td>\n",
       "      <td>0.738452</td>\n",
       "      <td>...</td>\n",
       "      <td>1.448438</td>\n",
       "      <td>1.725171</td>\n",
       "      <td>-1.033339</td>\n",
       "      <td>-0.133101</td>\n",
       "      <td>1.061274</td>\n",
       "      <td>-0.154184</td>\n",
       "      <td>1.971001</td>\n",
       "      <td>-1.235631</td>\n",
       "      <td>1.529797</td>\n",
       "      <td>0.732462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>481</th>\n",
       "      <td>82.209.194.12</td>\n",
       "      <td>0.762419</td>\n",
       "      <td>-0.345402</td>\n",
       "      <td>1.014703</td>\n",
       "      <td>1.906878</td>\n",
       "      <td>0.526492</td>\n",
       "      <td>-0.037594</td>\n",
       "      <td>1.308204</td>\n",
       "      <td>0.113156</td>\n",
       "      <td>-1.044283</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.063081</td>\n",
       "      <td>0.820639</td>\n",
       "      <td>1.027970</td>\n",
       "      <td>-0.017767</td>\n",
       "      <td>0.630199</td>\n",
       "      <td>1.957057</td>\n",
       "      <td>0.727005</td>\n",
       "      <td>0.944635</td>\n",
       "      <td>-0.984310</td>\n",
       "      <td>0.043586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482</th>\n",
       "      <td>62.118.200.4</td>\n",
       "      <td>-1.156053</td>\n",
       "      <td>1.434751</td>\n",
       "      <td>1.525660</td>\n",
       "      <td>0.979908</td>\n",
       "      <td>-0.768975</td>\n",
       "      <td>1.308144</td>\n",
       "      <td>0.612511</td>\n",
       "      <td>0.513437</td>\n",
       "      <td>2.410969</td>\n",
       "      <td>...</td>\n",
       "      <td>0.919892</td>\n",
       "      <td>0.958428</td>\n",
       "      <td>1.632860</td>\n",
       "      <td>0.760952</td>\n",
       "      <td>0.193747</td>\n",
       "      <td>-1.143165</td>\n",
       "      <td>0.756643</td>\n",
       "      <td>0.447346</td>\n",
       "      <td>0.700523</td>\n",
       "      <td>0.907617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>58898</td>\n",
       "      <td>0.520808</td>\n",
       "      <td>-0.932710</td>\n",
       "      <td>-0.316343</td>\n",
       "      <td>0.713410</td>\n",
       "      <td>0.892375</td>\n",
       "      <td>0.272136</td>\n",
       "      <td>0.236344</td>\n",
       "      <td>-2.365370</td>\n",
       "      <td>0.530122</td>\n",
       "      <td>...</td>\n",
       "      <td>1.200608</td>\n",
       "      <td>1.029859</td>\n",
       "      <td>0.572787</td>\n",
       "      <td>0.596633</td>\n",
       "      <td>0.880553</td>\n",
       "      <td>-0.456779</td>\n",
       "      <td>-1.522336</td>\n",
       "      <td>0.601182</td>\n",
       "      <td>0.549563</td>\n",
       "      <td>-0.629694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>484</th>\n",
       "      <td>194.129.65.79</td>\n",
       "      <td>0.037070</td>\n",
       "      <td>1.251953</td>\n",
       "      <td>-0.505659</td>\n",
       "      <td>-0.306981</td>\n",
       "      <td>-0.445666</td>\n",
       "      <td>-1.240538</td>\n",
       "      <td>1.452208</td>\n",
       "      <td>-1.959188</td>\n",
       "      <td>1.249311</td>\n",
       "      <td>...</td>\n",
       "      <td>0.849595</td>\n",
       "      <td>1.570504</td>\n",
       "      <td>0.716646</td>\n",
       "      <td>1.551721</td>\n",
       "      <td>2.108350</td>\n",
       "      <td>-0.124094</td>\n",
       "      <td>-0.341437</td>\n",
       "      <td>1.197091</td>\n",
       "      <td>0.800233</td>\n",
       "      <td>1.122424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>485</th>\n",
       "      <td>23065</td>\n",
       "      <td>1.976641</td>\n",
       "      <td>1.360819</td>\n",
       "      <td>-0.334303</td>\n",
       "      <td>0.090869</td>\n",
       "      <td>-0.205770</td>\n",
       "      <td>1.258431</td>\n",
       "      <td>-1.343815</td>\n",
       "      <td>0.271244</td>\n",
       "      <td>0.441873</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.120128</td>\n",
       "      <td>-0.170291</td>\n",
       "      <td>1.050155</td>\n",
       "      <td>0.934928</td>\n",
       "      <td>0.739351</td>\n",
       "      <td>-0.522270</td>\n",
       "      <td>1.415025</td>\n",
       "      <td>1.503070</td>\n",
       "      <td>2.350178</td>\n",
       "      <td>-0.386273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>2.32.222.83</td>\n",
       "      <td>-0.136150</td>\n",
       "      <td>-0.162737</td>\n",
       "      <td>2.106257</td>\n",
       "      <td>2.243745</td>\n",
       "      <td>-0.286995</td>\n",
       "      <td>-1.063059</td>\n",
       "      <td>-0.027266</td>\n",
       "      <td>-0.749125</td>\n",
       "      <td>1.116951</td>\n",
       "      <td>...</td>\n",
       "      <td>0.708253</td>\n",
       "      <td>0.292858</td>\n",
       "      <td>3.067321</td>\n",
       "      <td>-0.133252</td>\n",
       "      <td>2.238580</td>\n",
       "      <td>-0.078204</td>\n",
       "      <td>1.241414</td>\n",
       "      <td>1.944163</td>\n",
       "      <td>1.695636</td>\n",
       "      <td>0.604622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>2.159.25.101</td>\n",
       "      <td>1.357315</td>\n",
       "      <td>-0.323261</td>\n",
       "      <td>0.389804</td>\n",
       "      <td>1.018375</td>\n",
       "      <td>-0.156302</td>\n",
       "      <td>1.423718</td>\n",
       "      <td>2.017911</td>\n",
       "      <td>1.703387</td>\n",
       "      <td>2.288609</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.552473</td>\n",
       "      <td>-0.124275</td>\n",
       "      <td>1.417397</td>\n",
       "      <td>0.104926</td>\n",
       "      <td>0.146327</td>\n",
       "      <td>0.478318</td>\n",
       "      <td>1.097450</td>\n",
       "      <td>0.203244</td>\n",
       "      <td>0.328033</td>\n",
       "      <td>1.583722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>195.18.192.176</td>\n",
       "      <td>0.153705</td>\n",
       "      <td>1.283290</td>\n",
       "      <td>-0.190812</td>\n",
       "      <td>-0.228589</td>\n",
       "      <td>1.933350</td>\n",
       "      <td>-0.611409</td>\n",
       "      <td>1.264764</td>\n",
       "      <td>-0.484654</td>\n",
       "      <td>-1.237658</td>\n",
       "      <td>...</td>\n",
       "      <td>0.171497</td>\n",
       "      <td>-0.079376</td>\n",
       "      <td>0.772467</td>\n",
       "      <td>-0.618466</td>\n",
       "      <td>0.778640</td>\n",
       "      <td>-0.686686</td>\n",
       "      <td>1.939673</td>\n",
       "      <td>1.449313</td>\n",
       "      <td>0.049227</td>\n",
       "      <td>-0.049638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>54239</td>\n",
       "      <td>0.164561</td>\n",
       "      <td>0.253929</td>\n",
       "      <td>-0.947606</td>\n",
       "      <td>0.323797</td>\n",
       "      <td>0.890117</td>\n",
       "      <td>-1.837944</td>\n",
       "      <td>2.202500</td>\n",
       "      <td>0.973528</td>\n",
       "      <td>0.999811</td>\n",
       "      <td>...</td>\n",
       "      <td>2.937683</td>\n",
       "      <td>1.879506</td>\n",
       "      <td>-1.385982</td>\n",
       "      <td>-0.371252</td>\n",
       "      <td>1.971410</td>\n",
       "      <td>1.243892</td>\n",
       "      <td>0.518827</td>\n",
       "      <td>0.775615</td>\n",
       "      <td>1.666218</td>\n",
       "      <td>0.047914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>213.233.154.226</td>\n",
       "      <td>0.306673</td>\n",
       "      <td>1.134420</td>\n",
       "      <td>1.016805</td>\n",
       "      <td>-0.250786</td>\n",
       "      <td>0.198919</td>\n",
       "      <td>-0.814838</td>\n",
       "      <td>2.093996</td>\n",
       "      <td>0.395389</td>\n",
       "      <td>0.773094</td>\n",
       "      <td>...</td>\n",
       "      <td>0.071558</td>\n",
       "      <td>0.210263</td>\n",
       "      <td>2.696557</td>\n",
       "      <td>-0.026955</td>\n",
       "      <td>2.220162</td>\n",
       "      <td>0.536091</td>\n",
       "      <td>0.134274</td>\n",
       "      <td>1.343407</td>\n",
       "      <td>1.620327</td>\n",
       "      <td>1.458775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>116.50.166.74</td>\n",
       "      <td>0.580738</td>\n",
       "      <td>1.283427</td>\n",
       "      <td>0.736736</td>\n",
       "      <td>1.105664</td>\n",
       "      <td>-1.369499</td>\n",
       "      <td>0.369356</td>\n",
       "      <td>2.955257</td>\n",
       "      <td>1.098561</td>\n",
       "      <td>-0.581179</td>\n",
       "      <td>...</td>\n",
       "      <td>0.962231</td>\n",
       "      <td>1.055636</td>\n",
       "      <td>2.621310</td>\n",
       "      <td>1.334754</td>\n",
       "      <td>-0.398147</td>\n",
       "      <td>1.062035</td>\n",
       "      <td>0.516952</td>\n",
       "      <td>0.653140</td>\n",
       "      <td>-1.855200</td>\n",
       "      <td>0.338383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>26388</td>\n",
       "      <td>0.102267</td>\n",
       "      <td>0.612262</td>\n",
       "      <td>0.771484</td>\n",
       "      <td>1.596708</td>\n",
       "      <td>-0.755491</td>\n",
       "      <td>-0.020756</td>\n",
       "      <td>0.869510</td>\n",
       "      <td>-0.774466</td>\n",
       "      <td>0.216021</td>\n",
       "      <td>...</td>\n",
       "      <td>1.412328</td>\n",
       "      <td>0.391531</td>\n",
       "      <td>1.687438</td>\n",
       "      <td>0.944980</td>\n",
       "      <td>1.535072</td>\n",
       "      <td>1.049904</td>\n",
       "      <td>0.690480</td>\n",
       "      <td>0.684381</td>\n",
       "      <td>2.141122</td>\n",
       "      <td>2.161071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>195.250.146.100</td>\n",
       "      <td>-2.002915</td>\n",
       "      <td>0.858303</td>\n",
       "      <td>0.917466</td>\n",
       "      <td>-0.566871</td>\n",
       "      <td>2.046896</td>\n",
       "      <td>-0.274550</td>\n",
       "      <td>0.742508</td>\n",
       "      <td>0.389339</td>\n",
       "      <td>-0.348898</td>\n",
       "      <td>...</td>\n",
       "      <td>2.332419</td>\n",
       "      <td>-0.673239</td>\n",
       "      <td>2.208164</td>\n",
       "      <td>-0.051514</td>\n",
       "      <td>-0.528660</td>\n",
       "      <td>-0.673014</td>\n",
       "      <td>2.263793</td>\n",
       "      <td>0.592044</td>\n",
       "      <td>1.243944</td>\n",
       "      <td>-0.357567</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>494 rows × 101 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                word        x1        x2        x3        x4        x5  \\\n",
       "0       147.32.84.21 -0.897331  1.038339  1.168860  0.548789  0.827424   \n",
       "1               2759 -0.075689  0.664055  0.069890  0.113492  2.075718   \n",
       "2      203.125.50.50  0.481225  1.797862  0.638515  2.243348  2.395608   \n",
       "3        46.158.48.2  1.809672  1.160131  1.087142  2.002876 -0.088767   \n",
       "4     74.125.232.214  1.315566  1.503721  2.319758 -1.417383  1.881753   \n",
       "5       76.13.114.90  0.884432  1.402307  0.236475  2.755326  0.007849   \n",
       "6              51572  0.514282  0.252563  0.499660 -1.839670  0.198935   \n",
       "7      86.161.84.198  1.797912  0.926325  0.284184  0.353122 -1.392520   \n",
       "8        178.4.36.49  0.069732  0.804143 -0.327944  3.628991  0.595381   \n",
       "9              52316  1.228511  0.638138  1.316916  0.701257 -0.010153   \n",
       "10      58.8.226.198  1.281058 -0.048206 -0.118079  0.842407  0.978136   \n",
       "11             51019  2.035955  0.742344  0.416864  0.279828  1.844127   \n",
       "12              5318  1.634803  0.479017  0.471255 -0.310757  1.138414   \n",
       "13             31518 -0.840729  2.473368  1.024202  0.609309  0.256692   \n",
       "14      147.32.84.68 -0.492344  1.115174  1.055364  1.460472 -0.798470   \n",
       "15     69.204.160.28  0.700052  2.226423  0.624228  0.962537  2.419705   \n",
       "16     192.166.145.6  1.026075 -0.058727 -0.519893 -0.542104  2.260275   \n",
       "17             13363  2.096406  0.705950  0.413979  0.763562  0.583909   \n",
       "18    67.160.121.194 -0.111775  0.087736  0.799324 -0.026580  0.446313   \n",
       "19    95.149.168.251  0.794601  2.492112  3.919671  1.833806 -2.033913   \n",
       "20     94.198.111.82  1.096221  0.328939  0.950791 -0.164715  1.637892   \n",
       "21     147.32.84.165 -0.309435 -0.083729  1.227499  0.647278  2.346717   \n",
       "22     95.227.158.77 -0.711570 -1.102459  1.273976 -0.570579  0.671618   \n",
       "23              4793  0.995035  0.507893  0.570114  1.245277 -0.398104   \n",
       "24              6911  1.646036  1.222038 -1.086776  0.754388  0.252542   \n",
       "25     88.160.241.60 -0.401752  1.393662 -0.264355 -1.247841  0.628896   \n",
       "26    203.99.179.112  0.630424 -1.223904 -0.019807  0.645410  0.436549   \n",
       "27      88.193.88.76 -1.393651  0.012959  0.364322  0.485375 -0.398019   \n",
       "28              8000  3.634563  0.281187 -0.160636  0.189392  1.893791   \n",
       "29       129.6.15.28  1.236948  0.742899  3.195211  1.673277 -0.593115   \n",
       "..               ...       ...       ...       ...       ...       ...   \n",
       "464            49341 -0.560395  1.384934  0.652766  0.067068  1.321013   \n",
       "465      147.32.85.5  0.631980  0.287335 -0.047633  1.396060  1.386269   \n",
       "466            30657 -0.397917  1.507463  0.810642  1.227995  1.592374   \n",
       "467    77.37.194.251  0.306267  0.584805  1.602183 -0.188734  2.252532   \n",
       "468    147.32.86.181 -0.093423  3.045312  0.627166  1.670614  1.362169   \n",
       "469            23018 -0.421325  0.289654  0.707819  1.335384  0.760092   \n",
       "470            40565  0.464585  2.713660  0.958501 -1.153836  1.077187   \n",
       "471             2774 -1.380675  0.972148  0.884002  1.488662  1.555927   \n",
       "472   213.226.244.55  0.565508  0.329057  0.009766  0.727189  1.323340   \n",
       "473     63.135.80.58  0.435012  1.702355 -0.503747  1.862051  1.102790   \n",
       "474  178.200.203.145 -0.339449  0.157356 -0.469916 -0.327818  0.426694   \n",
       "475   147.230.32.193  2.256637 -0.108752  1.839135  1.771634  1.101400   \n",
       "476      82.39.2.249  0.677403  0.243544  0.091746  0.725390  0.350245   \n",
       "477    147.32.84.184 -0.780081  1.613062 -0.544166  0.522955 -0.592126   \n",
       "478     147.32.96.45  1.760448  1.615042  1.492031 -0.370347  0.529419   \n",
       "479    94.179.93.205  0.670075  0.312818 -1.269048  0.214690  0.379805   \n",
       "480     90.183.39.86  0.934499 -1.561029  0.493987  0.009653  1.628919   \n",
       "481    82.209.194.12  0.762419 -0.345402  1.014703  1.906878  0.526492   \n",
       "482     62.118.200.4 -1.156053  1.434751  1.525660  0.979908 -0.768975   \n",
       "483            58898  0.520808 -0.932710 -0.316343  0.713410  0.892375   \n",
       "484    194.129.65.79  0.037070  1.251953 -0.505659 -0.306981 -0.445666   \n",
       "485            23065  1.976641  1.360819 -0.334303  0.090869 -0.205770   \n",
       "486      2.32.222.83 -0.136150 -0.162737  2.106257  2.243745 -0.286995   \n",
       "487     2.159.25.101  1.357315 -0.323261  0.389804  1.018375 -0.156302   \n",
       "488   195.18.192.176  0.153705  1.283290 -0.190812 -0.228589  1.933350   \n",
       "489            54239  0.164561  0.253929 -0.947606  0.323797  0.890117   \n",
       "490  213.233.154.226  0.306673  1.134420  1.016805 -0.250786  0.198919   \n",
       "491    116.50.166.74  0.580738  1.283427  0.736736  1.105664 -1.369499   \n",
       "492            26388  0.102267  0.612262  0.771484  1.596708 -0.755491   \n",
       "493  195.250.146.100 -2.002915  0.858303  0.917466 -0.566871  2.046896   \n",
       "\n",
       "           x6        x7        x8        x9    ...          x91       x92  \\\n",
       "0    1.350281  0.357317  0.151798 -1.203985    ...    -1.574610 -0.374309   \n",
       "1    1.165797  0.159236  0.656618  0.875231    ...     1.370241 -0.426580   \n",
       "2   -0.890352  2.302247  1.510286  0.544332    ...    -0.913163  0.649294   \n",
       "3    1.478506  0.157406  0.930297  1.370391    ...    -0.043075  1.327622   \n",
       "4    2.782334  0.656875  2.596758 -1.372827    ...     0.614940  2.182342   \n",
       "5    0.771038  1.154081  0.976132 -0.735547    ...     1.582394  0.975448   \n",
       "6    0.511351 -0.475192  0.597154  0.617414    ...     1.126984 -0.027641   \n",
       "7    0.440905 -0.164116  0.122449  0.317926    ...    -0.295164  3.241334   \n",
       "8    0.449587  1.073174  1.300431  0.638524    ...     0.760437  1.112388   \n",
       "9    1.492005  0.559310 -0.244314  0.325908    ...     2.468081  0.408820   \n",
       "10  -1.057679  1.108354  1.601815  0.421898    ...     0.882990  0.797763   \n",
       "11   1.160855  1.311611  1.634317  0.617606    ...     2.243950  1.576250   \n",
       "12   1.524524  0.897687  0.037149  1.442197    ...    -1.359259 -1.138771   \n",
       "13  -1.922309  0.097915  0.800605 -1.120466    ...     0.893394  0.391185   \n",
       "14   0.730227 -0.163092  1.801228 -0.208467    ...     2.950172  0.613158   \n",
       "15   1.702399  2.758665  3.549597  0.303176    ...    -0.050712  0.357555   \n",
       "16   0.881187  0.720510 -0.660529 -1.195983    ...     1.668018 -0.046117   \n",
       "17   0.168505  1.447062 -0.846526  1.660644    ...    -1.494039 -0.812372   \n",
       "18   1.088098  1.565305  1.297442  1.692738    ...    -0.989083 -0.032097   \n",
       "19  -0.362740  1.396368  0.648457  1.919550    ...    -1.557867  0.666718   \n",
       "20  -0.043121  1.054474  0.211266  0.950749    ...     1.012828 -0.152538   \n",
       "21   2.903686  0.198202  0.852055  0.316594    ...     0.909025  0.682161   \n",
       "22   0.664352  0.108834 -0.234763 -1.795768    ...     0.127483  0.221906   \n",
       "23   0.079663 -0.767815  1.476544  0.028334    ...     1.096818  1.566755   \n",
       "24   1.333300  2.129134  0.298845  0.608951    ...    -1.171739  1.331473   \n",
       "25   1.218504  1.769800  2.143489  0.840108    ...     0.785203  0.591842   \n",
       "26   1.846159 -0.381286  0.368831  1.227113    ...     0.155704  0.151103   \n",
       "27  -0.495255  0.774709  1.462987  0.319939    ...    -0.217846  0.282672   \n",
       "28   0.802488 -1.097765  1.989843  0.434401    ...    -0.827450  0.525488   \n",
       "29   1.026407  0.772482 -0.812714  1.110485    ...     0.953716  0.147812   \n",
       "..        ...       ...       ...       ...    ...          ...       ...   \n",
       "464 -0.759749 -1.050181 -0.118862  0.214881    ...    -0.165074  0.912992   \n",
       "465  0.940499  1.096772  0.769486 -0.621018    ...     0.701355  0.325464   \n",
       "466  0.620145 -1.290038  0.676622  0.222824    ...    -0.863809  1.855566   \n",
       "467  1.230337  1.279994  1.540911  0.067135    ...     0.463550 -0.847110   \n",
       "468  0.499756 -2.100547  0.650885  0.342686    ...     1.760501  1.271749   \n",
       "469  0.886493  0.853310  1.703280  0.191816    ...     0.517908 -0.090548   \n",
       "470 -0.716174  0.189335 -0.997213 -0.346337    ...     0.952650  1.040361   \n",
       "471  2.954420  1.037272 -1.002583  0.359337    ...     0.003577  0.072338   \n",
       "472  1.877180  0.333364  1.087386  0.457730    ...    -1.036515  0.118572   \n",
       "473  0.051772  2.722988 -1.114797 -0.447549    ...     0.334260  0.809752   \n",
       "474  0.585979  0.592479 -1.341660 -0.088474    ...     0.036497 -1.378752   \n",
       "475  2.210413  0.671699 -0.045613  2.174083    ...     0.166658  1.888095   \n",
       "476  0.493425  0.560017  0.853640  0.018194    ...     1.168239 -0.349057   \n",
       "477  1.947488  1.837972  0.325368 -0.343267    ...     1.434790 -0.035994   \n",
       "478  1.685722 -0.543488  0.541772  0.231811    ...     2.265574  1.610020   \n",
       "479  1.201938 -0.798355  0.816026  2.721569    ...     1.502677 -0.418117   \n",
       "480 -0.732768  1.595065  1.262217  0.738452    ...     1.448438  1.725171   \n",
       "481 -0.037594  1.308204  0.113156 -1.044283    ...    -0.063081  0.820639   \n",
       "482  1.308144  0.612511  0.513437  2.410969    ...     0.919892  0.958428   \n",
       "483  0.272136  0.236344 -2.365370  0.530122    ...     1.200608  1.029859   \n",
       "484 -1.240538  1.452208 -1.959188  1.249311    ...     0.849595  1.570504   \n",
       "485  1.258431 -1.343815  0.271244  0.441873    ...    -0.120128 -0.170291   \n",
       "486 -1.063059 -0.027266 -0.749125  1.116951    ...     0.708253  0.292858   \n",
       "487  1.423718  2.017911  1.703387  2.288609    ...    -0.552473 -0.124275   \n",
       "488 -0.611409  1.264764 -0.484654 -1.237658    ...     0.171497 -0.079376   \n",
       "489 -1.837944  2.202500  0.973528  0.999811    ...     2.937683  1.879506   \n",
       "490 -0.814838  2.093996  0.395389  0.773094    ...     0.071558  0.210263   \n",
       "491  0.369356  2.955257  1.098561 -0.581179    ...     0.962231  1.055636   \n",
       "492 -0.020756  0.869510 -0.774466  0.216021    ...     1.412328  0.391531   \n",
       "493 -0.274550  0.742508  0.389339 -0.348898    ...     2.332419 -0.673239   \n",
       "\n",
       "          x93       x94       x95       x96       x97       x98       x99  \\\n",
       "0   -1.090475 -0.190525  2.256838 -0.995346  0.318381  1.069325  1.856886   \n",
       "1   -1.050216 -0.632900 -0.132972  1.833304 -0.565339  0.518230  0.939395   \n",
       "2    0.177525  1.998903  1.194582  1.538517  0.798135  0.509123  1.118166   \n",
       "3    2.011404 -0.581754  0.221714  2.069015 -0.875224  0.027485  0.830814   \n",
       "4    2.397736  2.521049  1.555292 -0.858441  1.286282  1.166821  2.559523   \n",
       "5   -0.361619  1.121443  0.167561 -0.635591  2.206366 -1.205090  1.419789   \n",
       "6   -0.332207 -0.307638 -0.472292  1.690702  0.915639  1.314826  0.630894   \n",
       "7    0.917003  1.322532  0.547080  2.294626  1.474384  3.063208 -0.506767   \n",
       "8    0.236854  0.439323 -0.180617  1.338692 -0.215818  0.643084 -0.074870   \n",
       "9    1.113907 -0.232438  0.813623  0.449509 -0.330448  0.034572  0.109383   \n",
       "10   0.473813  0.640113  0.718233  0.106448  1.319540  0.065148 -0.532863   \n",
       "11   1.415075 -0.635900  1.021015  1.229937 -0.416690 -1.454134  0.647077   \n",
       "12   0.989995  2.509193 -0.763102  0.929420 -0.336079  1.183128  0.309567   \n",
       "13  -1.375062  0.994655  1.439185  1.416438  0.755577 -0.317367  1.747638   \n",
       "14   0.819825  0.633704 -0.005961  1.537209 -0.623843 -0.683515  0.444648   \n",
       "15   1.031685  0.900700  0.401323  1.497588  1.041961 -0.019976  0.229779   \n",
       "16   1.940023  0.952853  1.809393 -1.978976  1.316869  2.241636  0.671727   \n",
       "17  -0.023997  1.410699  1.910866  0.246955  0.505665  0.780509 -0.183022   \n",
       "18   1.096282  2.349863  1.262412  0.899494  0.114332  0.078487 -1.289155   \n",
       "19   1.132561  0.795950  1.500481  0.349687  1.254174 -0.451241 -1.217628   \n",
       "20   1.234861 -0.281867  1.400402  1.061536 -0.710520  0.075572  2.412917   \n",
       "21  -1.031873 -0.016099  0.923578  1.791329  0.823432  0.490277  2.273566   \n",
       "22   1.853326  1.432049  1.936878 -0.544655  0.953155 -0.455121  2.038569   \n",
       "23   0.881113  1.823620  1.657318 -0.278470  1.513502  1.536893  1.759382   \n",
       "24   2.125358  0.300442  0.556368  1.604478  0.629327  1.609062  1.146542   \n",
       "25   0.147244  0.828669  1.243851  2.061680 -0.009819  1.077649 -0.328895   \n",
       "26   1.481954  0.531424  0.774768 -0.102970 -0.429105  0.615498 -0.214952   \n",
       "27  -0.411379  0.561824 -0.723491  0.202327 -0.121119 -0.241870  0.082464   \n",
       "28   0.845032 -0.298382  2.185773  1.281961 -0.537364  2.507885  0.404093   \n",
       "29   0.996055 -0.381551  0.151098  0.663533  1.689116  2.134418  0.341748   \n",
       "..        ...       ...       ...       ...       ...       ...       ...   \n",
       "464  1.202617  1.434320  0.417483  0.237063  0.600661  0.059620 -1.329937   \n",
       "465 -0.164755  0.956906  1.612222  0.700450  0.880975  0.569095  0.289293   \n",
       "466 -0.973069  0.458452 -1.135749  1.257886  0.182025  0.826035  0.498840   \n",
       "467  0.418904  1.269640 -0.350296  1.703498  0.696683  2.041790  1.265325   \n",
       "468  1.833856  0.231285  2.110642  0.939919  1.369057  0.559837  1.538809   \n",
       "469 -0.141383  1.501319  2.250376 -0.146305  0.840294  0.477808 -0.133752   \n",
       "470  0.019764  0.850117  0.015107  2.429726  1.637238  0.068725  0.063951   \n",
       "471  2.048658  0.518016  0.962703  0.231017  0.737300 -0.284791  0.463807   \n",
       "472  0.518128  1.172096  0.486083  1.267681 -0.828938  0.566484  2.679336   \n",
       "473 -0.682559  0.376691  0.972959  0.504591  1.597688  0.982895 -0.411875   \n",
       "474  1.807538 -0.498600  0.745016 -1.530732 -0.189081 -0.605807 -2.014765   \n",
       "475 -0.408383  1.317657  0.765628 -0.492492  1.923769  1.814411 -0.896296   \n",
       "476 -0.305170  0.235523 -0.565100 -0.036158  2.410828  2.043656  1.751138   \n",
       "477  0.187794  1.394603  2.655153 -0.064278  2.555540 -0.128795 -0.789245   \n",
       "478 -0.460652 -0.662355 -0.394565  1.273404  0.347328  1.367844  1.141068   \n",
       "479  0.932822  1.010649  1.592667  0.024429  1.631352  0.036423 -0.029284   \n",
       "480 -1.033339 -0.133101  1.061274 -0.154184  1.971001 -1.235631  1.529797   \n",
       "481  1.027970 -0.017767  0.630199  1.957057  0.727005  0.944635 -0.984310   \n",
       "482  1.632860  0.760952  0.193747 -1.143165  0.756643  0.447346  0.700523   \n",
       "483  0.572787  0.596633  0.880553 -0.456779 -1.522336  0.601182  0.549563   \n",
       "484  0.716646  1.551721  2.108350 -0.124094 -0.341437  1.197091  0.800233   \n",
       "485  1.050155  0.934928  0.739351 -0.522270  1.415025  1.503070  2.350178   \n",
       "486  3.067321 -0.133252  2.238580 -0.078204  1.241414  1.944163  1.695636   \n",
       "487  1.417397  0.104926  0.146327  0.478318  1.097450  0.203244  0.328033   \n",
       "488  0.772467 -0.618466  0.778640 -0.686686  1.939673  1.449313  0.049227   \n",
       "489 -1.385982 -0.371252  1.971410  1.243892  0.518827  0.775615  1.666218   \n",
       "490  2.696557 -0.026955  2.220162  0.536091  0.134274  1.343407  1.620327   \n",
       "491  2.621310  1.334754 -0.398147  1.062035  0.516952  0.653140 -1.855200   \n",
       "492  1.687438  0.944980  1.535072  1.049904  0.690480  0.684381  2.141122   \n",
       "493  2.208164 -0.051514 -0.528660 -0.673014  2.263793  0.592044  1.243944   \n",
       "\n",
       "         x100  \n",
       "0    1.841685  \n",
       "1    1.825040  \n",
       "2   -0.096901  \n",
       "3    1.676701  \n",
       "4    0.647945  \n",
       "5    0.983787  \n",
       "6    0.845138  \n",
       "7    0.645493  \n",
       "8    0.236419  \n",
       "9    2.235850  \n",
       "10   1.689204  \n",
       "11  -0.349333  \n",
       "12  -0.632391  \n",
       "13  -0.545176  \n",
       "14   1.768843  \n",
       "15   0.870451  \n",
       "16   0.641895  \n",
       "17  -0.368206  \n",
       "18   1.302531  \n",
       "19   0.548110  \n",
       "20   1.420767  \n",
       "21  -0.346761  \n",
       "22  -0.114402  \n",
       "23   1.254017  \n",
       "24   1.643509  \n",
       "25   0.055718  \n",
       "26  -0.679337  \n",
       "27  -1.972011  \n",
       "28   0.650131  \n",
       "29   0.281706  \n",
       "..        ...  \n",
       "464 -0.668846  \n",
       "465  0.764740  \n",
       "466  0.790112  \n",
       "467  0.887201  \n",
       "468  0.008279  \n",
       "469  0.374254  \n",
       "470  1.211536  \n",
       "471  1.571767  \n",
       "472 -0.818379  \n",
       "473 -0.911888  \n",
       "474  1.142302  \n",
       "475  0.219959  \n",
       "476  1.910241  \n",
       "477  1.949822  \n",
       "478  0.966821  \n",
       "479  3.236291  \n",
       "480  0.732462  \n",
       "481  0.043586  \n",
       "482  0.907617  \n",
       "483 -0.629694  \n",
       "484  1.122424  \n",
       "485 -0.386273  \n",
       "486  0.604622  \n",
       "487  1.583722  \n",
       "488 -0.049638  \n",
       "489  0.047914  \n",
       "490  1.458775  \n",
       "491  0.338383  \n",
       "492  2.161071  \n",
       "493 -0.357567  \n",
       "\n",
       "[494 rows x 101 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w2v_df = pd.DataFrame(vectors, columns = [\"x\"+str(i) for i in range(1,101) ])\n",
    "w2v_df['word'] = wordlist\n",
    "head_list = [\"x\"+str(i) for i in range(1,101)]\n",
    "w2v_df = w2v_df[['word']+head_list]\n",
    "w2v_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  74.76884 -451.4918 ]\n",
      "[  35.09708 -367.3498 ]\n",
      "[-129.68605 -312.05222]\n",
      "[95.13056  -8.323978]\n",
      "[-157.8267  270.0755]\n",
      "[ 95.56532 160.12128]\n",
      "[-320.71838    -8.932512]\n",
      "[-195.17259     -6.8093147]\n",
      "[ 87.014496 186.62857 ]\n",
      "[ 34.604824 240.27507 ]\n",
      "[185.04834 182.55054]\n",
      "[ -5.844442 268.34055 ]\n",
      "[142.39273  76.39634]\n",
      "[429.8281   97.70992]\n",
      "[-90.11668    3.103189]\n",
      "[122.03537 136.85425]\n",
      "[-44.358692 321.77667 ]\n",
      "[-279.01566 -317.61884]\n",
      "[24.103407 59.131786]\n",
      "[  29.285057 -419.70032 ]\n",
      "[-430.32703     9.157623]\n",
      "[  63.710934 -314.6968  ]\n",
      "[-97.784096 185.29616 ]\n",
      "[ -18.352783 -224.38705 ]\n",
      "[ 162.38173 -126.72485]\n",
      "[-118.18076   -63.282314]\n",
      "[45.803596 51.286064]\n",
      "[-284.48553  -78.71149]\n",
      "[ 257.8976  -110.71007]\n",
      "[-59.14961 208.3205 ]\n",
      "[-178.53412 -309.22687]\n",
      "[-15.936785 -37.50085 ]\n",
      "[ 116.05604 -217.71886]\n",
      "[-210.04333  248.28825]\n",
      "[-236.8781  -130.28705]\n",
      "[-158.97853    37.262886]\n",
      "[-414.05792    85.284935]\n",
      "[-65.13633  -63.522514]\n",
      "[ 305.93878 -273.11337]\n",
      "[  30.53971 -347.1384 ]\n",
      "[-22.29514 199.23158]\n",
      "[149.2148  167.51845]\n",
      "[ 54.358574 111.61185 ]\n",
      "[ 72.738976 -60.126507]\n",
      "[-263.46655   -11.531818]\n",
      "[-172.20175   -21.086603]\n",
      "[-196.11021  -85.39557]\n",
      "[-311.27115  173.86462]\n",
      "[-105.401146  152.76363 ]\n",
      "[-398.87628  185.6085 ]\n",
      "[-200.9432  -437.96136]\n",
      "[-43.534714 268.84378 ]\n",
      "[282.05206 231.33952]\n",
      "[ -10.99477 -362.69156]\n",
      "[  77.75685 -126.67175]\n",
      "[-161.88397  -50.87619]\n",
      "[-197.25145  198.98166]\n",
      "[ 51.62015 144.98596]\n",
      "[69.72359 31.97221]\n",
      "[   1.881052 -196.32628 ]\n",
      "[-136.05878    83.682335]\n",
      "[269.77985 285.16135]\n",
      "[-264.8343     62.513268]\n",
      "[-222.99197 -158.80838]\n",
      "[-14.4911785 105.27386  ]\n",
      "[ 32.781433 175.07195 ]\n",
      "[216.75969 315.8665 ]\n",
      "[ -88.76175 -319.64316]\n",
      "[ 221.76122 -260.16553]\n",
      "[  99.64616 -136.35547]\n",
      "[ -66.7979  -203.96312]\n",
      "[-124.60064   -10.375001]\n",
      "[ 105.54893 -298.41205]\n",
      "[-162.5028  -228.26851]\n",
      "[-115.96565  362.19662]\n",
      "[152.8436 133.0534]\n",
      "[ 118.40742 -155.41418]\n",
      "[251.59215 -80.07739]\n",
      "[ 311.62234 -167.75018]\n",
      "[-204.13733 -118.29717]\n",
      "[ 298.48126 -124.95239]\n",
      "[-266.0746  171.2186]\n",
      "[-346.8257  -182.70856]\n",
      "[  84.94028 -108.42692]\n",
      "[-172.9178   229.59727]\n",
      "[  69.87432 -147.36623]\n",
      "[-316.47925 -147.4789 ]\n",
      "[-163.03708    -1.691261]\n",
      "[263.66052   44.682095]\n",
      "[-41.47899 142.18169]\n",
      "[-257.84885  -98.55562]\n",
      "[  6.787828 180.46704 ]\n",
      "[141.00618 -99.95085]\n",
      "[ 22.674276 -57.2252  ]\n",
      "[-51.54466  58.89328]\n",
      "[-448.7974     34.812675]\n",
      "[-119.29067 -138.95975]\n",
      "[ 195.11986 -134.48694]\n",
      "[-71.74584 313.06088]\n",
      "[-223.05127   122.883446]\n",
      "[ 42.13151 -82.44814]\n",
      "[-170.1775  -393.08533]\n",
      "[-293.06503  133.2033 ]\n",
      "[-34.628464  18.416132]\n",
      "[66.55798 69.35554]\n",
      "[ -58.33681 -113.9813 ]\n",
      "[ -85.58993 -133.133  ]\n",
      "[-37.575775  -2.500716]\n",
      "[-4.0614862 81.95068  ]\n",
      "[-124.39852 -452.3139 ]\n",
      "[-170.52127  -111.032646]\n",
      "[-374.92902 -241.2165 ]\n",
      "[265.2402    86.762985]\n",
      "[ -98.58869 -280.2451 ]\n",
      "[ 267.36023 -149.64006]\n",
      "[311.54993 186.09114]\n",
      "[-21.475286 122.72664 ]\n",
      "[ 43.808533 -58.721027]\n",
      "[-190.8273    -37.535164]\n",
      "[-6.678196 35.77295 ]\n",
      "[197.83731 274.5243 ]\n",
      "[ -31.749296 -209.69508 ]\n",
      "[-267.21875 -149.97699]\n",
      "[-273.18802   -22.653093]\n",
      "[-12.885034 153.56001 ]\n",
      "[  83.35216 -388.43298]\n",
      "[-400.56427 -192.101  ]\n",
      "[-267.93665 -226.19171]\n",
      "[261.04984    4.154603]\n",
      "[  48.031544 -123.38987 ]\n",
      "[ 86.959366 213.95174 ]\n",
      "[-352.5017  144.6103]\n",
      "[ -32.851604 -156.72087 ]\n",
      "[ 59.479465 201.82365 ]\n",
      "[ 10.125785 -38.609962]\n",
      "[308.90326  -47.890507]\n",
      "[-140.60323     8.030793]\n",
      "[  4.1211247 130.97925  ]\n",
      "[ -52.65892 -226.58379]\n",
      "[-105.89173  256.67764]\n",
      "[-101.92961 -160.25293]\n",
      "[ -59.765602 -374.89392 ]\n",
      "[-278.43173   95.29584]\n",
      "[ 366.05673 -265.18027]\n",
      "[-100.47028 -204.82188]\n",
      "[327.45435 151.29323]\n",
      "[ 24.651604 210.45775 ]\n",
      "[ 267.32498 -190.89282]\n",
      "[-206.80936  160.76749]\n",
      "[-108.99122  133.35379]\n",
      "[ 39.29896 311.93423]\n",
      "[305.0404   81.27532]\n",
      "[-295.4903    -43.708935]\n",
      "[111.643196 358.9787  ]\n",
      "[-18.050741   8.44144 ]\n",
      "[ 114.49727 -110.99352]\n",
      "[226.37537 102.58972]\n",
      "[ 69.89296  -25.578634]\n",
      "[119.10134   67.313225]\n",
      "[ -50.190296 -335.72897 ]\n",
      "[ 67.45511 171.18863]\n",
      "[96.4674   18.465015]\n",
      "[-279.085   -272.83133]\n",
      "[-289.37943    35.072655]\n",
      "[90.83929  74.438805]\n",
      "[291.46185  -15.615754]\n",
      "[  45.84023 -174.08482]\n",
      "[ -92.38389  -107.201546]\n",
      "[113.585434 201.07532 ]\n",
      "[  -9.658669 -142.75485 ]\n",
      "[-151.59196   -22.490187]\n",
      "[394.56644   49.622353]\n",
      "[138.58727  105.584984]\n",
      "[144.56001  -56.661694]\n",
      "[ 34.331226 265.99377 ]\n",
      "[-222.36775   55.24434]\n",
      "[201.08243  81.09325]\n",
      "[35.396236 32.66201 ]\n",
      "[263.47565 181.9014 ]\n",
      "[ -36.59614 -182.27   ]\n",
      "[  0.8952501 230.92464  ]\n",
      "[-150.94077  200.87585]\n",
      "[ 134.31314 -181.86472]\n",
      "[235.86972  -19.728624]\n",
      "[-189.11761 -284.39066]\n",
      "[357.67026  87.55358]\n",
      "[  15.747188 -223.78198 ]\n",
      "[136.34451  40.53747]\n",
      "[-310.47668   66.92465]\n",
      "[-150.17041   63.52902]\n",
      "[73.0645   98.774635]\n",
      "[-231.37859 -259.3889 ]\n",
      "[-160.68835   113.920815]\n",
      "[  8.372223 -22.602213]\n",
      "[ -66.267395 -265.13586 ]\n",
      "[ 154.71043 -230.60118]\n",
      "[-111.70038 -364.73257]\n",
      "[-29.358057  81.10411 ]\n",
      "[141.21869 232.43153]\n",
      "[310.3593  105.33632]\n",
      "[  90.889336 -343.97226 ]\n",
      "[-119.87434   66.28087]\n",
      "[  19.948559 -176.933   ]\n",
      "[-236.6737  174.7776]\n",
      "[-145.49316 -120.34308]\n",
      "[-90.174225 -55.907692]\n",
      "[ -2.89639  -57.457443]\n",
      "[ -58.48253 -139.29463]\n",
      "[112.05208  90.34998]\n",
      "[-153.09839 -141.92065]\n",
      "[ 17.234932 102.80725 ]\n",
      "[  8.986637 -96.73862 ]\n",
      "[102.78253 113.3802 ]\n",
      "[-61.951603 -37.774834]\n",
      "[  79.91612 -224.12169]\n",
      "[ 192.43497 -234.92737]\n",
      "[440.39212 -94.93663]\n",
      "[328.625       2.1846473]\n",
      "[-363.352   -125.52068]\n",
      "[ 182.23976 -351.5805 ]\n",
      "[-374.28998  125.12303]\n",
      "[ 138.03174 -384.18497]\n",
      "[-144.53961  141.53148]\n",
      "[-115.17012 -113.13731]\n",
      "[182.90816 148.65646]\n",
      "[45.893356 87.08319 ]\n",
      "[-187.71542 -145.49986]\n",
      "[2.2070272e-01 3.3767346e+02]\n",
      "[-10.492885 -81.78593 ]\n",
      "[-97.30347  36.68665]\n",
      "[ 127.94035 -284.4345 ]\n",
      "[-366.8423   -72.54161]\n",
      "[-287.9627 -118.3003]\n",
      "[-239.20049  217.57248]\n",
      "[117.033035 283.84167 ]\n",
      "[-242.51581    93.243454]\n",
      "[-321.92242   99.54857]\n",
      "[-122.3122  -230.22794]\n",
      "[-226.32094 -217.84613]\n",
      "[79.02248  12.941588]\n",
      "[-351.60992 -321.68896]\n",
      "[ 306.0892  -333.30695]\n",
      "[147.54845    4.733935]\n",
      "[23.124138 19.67156 ]\n",
      "[ 263.90515 -237.07632]\n",
      "[124.2045   29.03177]\n",
      "[-35.711742 -95.91979 ]\n",
      "[159.2067   62.68918]\n",
      "[ 151.16646 -196.47987]\n",
      "[-177.76303   65.66366]\n",
      "[  71.381805 -177.40202 ]\n",
      "[-84.50376 275.8462 ]\n",
      "[ -89.95584 -413.83972]\n",
      "[ -6.199666 294.0286  ]\n",
      "[-68.72258 180.44823]\n",
      "[-418.61597  -82.75308]\n",
      "[-188.24959  104.41746]\n",
      "[255.15579 115.09968]\n",
      "[  49.33848 -240.65576]\n",
      "[ 76.21201 129.95753]\n",
      "[-113.12523  290.00537]\n",
      "[ -12.573379 -319.98373 ]\n",
      "[   3.9979587 -253.05894  ]\n",
      "[  97.67993 -174.01776]\n",
      "[151.02441 312.9433 ]\n",
      "[102.9506   46.86447]\n",
      "[-32.148735 174.23312 ]\n",
      "[ 139.5566  -446.33844]\n",
      "[ 61.76489 420.12518]\n",
      "[104.032486 246.1475  ]\n",
      "[ 410.33597 -149.10161]\n",
      "[-128.69987 -180.53008]\n",
      "[111.832596 -21.184238]\n",
      "[ 33.742508 -34.257656]\n",
      "[-263.46036    10.526807]\n",
      "[-233.28117 -291.0525 ]\n",
      "[  50.703133 -107.433334]\n",
      "[ 15.936998 -75.411064]\n",
      "[ 20.401455 157.42444 ]\n",
      "[-285.37567  214.26773]\n",
      "[-2.528327  -6.2751412]\n",
      "[ 223.39609  -117.408134]\n",
      "[11.755564 35.78684 ]\n",
      "[-17.402737 433.7422  ]\n",
      "[-123.33359   -91.365364]\n",
      "[ 353.5889  -152.24571]\n",
      "[138.37415  -27.018404]\n",
      "[ 195.66939 -400.69183]\n",
      "[ -73.88813 -164.50731]\n",
      "[-258.94455   -53.721325]\n",
      "[-323.74484   -99.354034]\n",
      "[ 183.90833 -166.65787]\n",
      "[368.896   -99.42894]\n",
      "[-122.43061 -253.7282 ]\n",
      "[ 312.38794 -219.63786]\n",
      "[-95.984314 353.28845 ]\n",
      "[-10.790697 -27.767437]\n",
      "[-31.224304 227.42984 ]\n",
      "[-81.8732   110.475296]\n",
      "[-95.76684  81.95929]\n",
      "[-149.62146  417.2758 ]\n",
      "[-153.15271 -270.01343]\n",
      "[-134.1005   245.74634]\n",
      "[372.26453    -6.2867627]\n",
      "[-43.90296  -22.240486]\n",
      "[375.914   198.67908]\n",
      "[294.17404   27.621824]\n",
      "[120.85202 -49.87227]\n",
      "[ 73.03981 281.04938]\n",
      "[ 133.87247 -335.28662]\n",
      "[-151.2618   317.91162]\n",
      "[-106.76397 -185.48465]\n",
      "[-197.98604  288.2596 ]\n",
      "[  93.009605 -253.76498 ]\n",
      "[ 91.45799  -40.969616]\n",
      "[   6.688047 -123.08607 ]\n",
      "[-379.35657  261.19122]\n",
      "[-478.03568   -39.149475]\n",
      "[-318.86945 -276.74548]\n",
      "[-437.45728  143.35458]\n",
      "[186.0428  229.02629]\n",
      "[375.7191  133.78026]\n",
      "[-73.461624 -16.388554]\n",
      "[-227.11124   -60.409004]\n",
      "[  47.86283 -146.73784]\n",
      "[-73.77131  -90.855934]\n",
      "[-380.97977   24.71574]\n",
      "[-51.190598  28.540094]\n",
      "[-23.623789 -15.460527]\n",
      "[73.39634 41.46296]\n",
      "[-132.39186  172.10397]\n",
      "[220.88464 162.93173]\n",
      "[-97.168045 215.74309 ]\n",
      "[158.83072   25.196383]\n",
      "[265.34366 156.74603]\n",
      "[220.59906 203.37035]\n",
      "[200.47914  -29.446545]\n",
      "[182.80563  114.793396]\n",
      "[ 4.385993 12.399236]\n",
      "[ 88.66687 319.8973 ]\n",
      "[ 126.89737 -247.83195]\n",
      "[  -9.706462 -171.94771 ]\n",
      "[  99.040184 -209.16661 ]\n",
      "[-232.92995    11.149279]\n",
      "[ -16.329643 -110.94386 ]\n",
      "[-198.06996   58.18575]\n",
      "[-298.14316    -9.628527]\n",
      "[-225.9861   -91.99221]\n",
      "[-245.58997 -183.95056]\n",
      "[-126.83277    36.923115]\n",
      "[-164.14017   93.81323]\n",
      "[  27.354485 -130.1564  ]\n",
      "[-305.95517  258.71738]\n",
      "[ 55.069878 -44.242188]\n",
      "[123.06008 -76.90456]\n",
      "[-42.704563 -47.988556]\n",
      "[-109.490776  108.307365]\n",
      "[101.09615 132.55812]\n",
      "[ 260.1374  -398.57388]\n",
      "[-242.08272  317.36386]\n",
      "[-39.90581 376.19632]\n",
      "[ -35.860123 -127.71184 ]\n",
      "[-342.73923  210.45062]\n",
      "[-315.8691  -223.53647]\n",
      "[ 366.86218 -203.38885]\n",
      "[  15.630227 -150.83    ]\n",
      "[180.6381    55.231667]\n",
      "[-25.198433  58.696438]\n",
      "[-359.00275   65.53102]\n",
      "[-96.05035  -79.472824]\n",
      "[-105.40362  649.4265 ]\n",
      "[-29.093674  36.304333]\n",
      "[ 217.69276 -180.77792]\n",
      "[ 212.20628 -305.06   ]\n",
      "[438.3582  817.40906]\n",
      "[119.28225    5.685662]\n",
      "[179.11847  -59.076424]\n",
      "[ 99.070496 -89.77137 ]\n",
      "[-32.673615 -70.96701 ]\n",
      "[-226.8287    -28.715008]\n",
      "[230.26811 -50.68025]\n",
      "[166.52716  91.26773]\n",
      "[334.98422   46.286034]\n",
      "[-170.73875    27.713663]\n",
      "[-58.620415    2.8048632]\n",
      "[-213.5129 -347.7212]\n",
      "[-169.13673  -81.10805]\n",
      "[-100.46787   -14.514749]\n",
      "[-62.66298  83.34382]\n",
      "[-185.82298  131.86961]\n",
      "[  39.597836 -205.41573 ]\n",
      "[234.42627 244.95032]\n",
      "[-69.15542 239.87605]\n",
      "[-211.06639    86.304565]\n",
      "[ 171.75845 -269.84085]\n",
      "[-189.7105   372.67496]\n",
      "[-254.53423  267.89743]\n",
      "[-111.9172      14.6645975]\n",
      "[163.71129 -82.42269]\n",
      "[ -55.85924 -176.529  ]\n",
      "[ 231.4525  -149.60374]\n",
      "[-188.05836 -200.98366]\n",
      "[-419.79047 -139.66829]\n",
      "[ 187.21092 -202.7256 ]\n",
      "[-184.39279  337.4429 ]\n",
      "[-54.40312 -81.6578 ]\n",
      "[ -26.674932 -418.4896  ]\n",
      "[116.74204 168.22905]\n",
      "[230.16661   23.763498]\n",
      "[-320.8422   312.05942]\n",
      "[-143.72615 -197.96265]\n",
      "[ 172.01094 -307.34113]\n",
      "[235.75462  65.80885]\n",
      "[ 153.63159 -157.43742]\n",
      "[44.406307 11.822669]\n",
      "[-268.411    369.70374]\n",
      "[-194.07295  -64.18927]\n",
      "[  66.92905 -275.67035]\n",
      "[154.28084 201.8478 ]\n",
      "[194.41212  -62.364075]\n",
      "[ -18.31911 -285.34207]\n",
      "[ 242.8149  -343.65817]\n",
      "[-89.48721  66.14137]\n",
      "[ 45.560535 -14.891143]\n",
      "[ 226.87158 -214.7589 ]\n",
      "[-74.33072  23.35572]\n",
      "[  27.53633 -102.69056]\n",
      "[154.63878 267.5677 ]\n",
      "[-83.77404 418.88193]\n",
      "[ 0.28386286 60.458668  ]\n",
      "[335.56866 243.78012]\n",
      "[-65.11631 121.1894 ]\n",
      "[-195.77737 -239.91843]\n",
      "[ 144.58714 -134.03285]\n",
      "[349.32547  -52.232323]\n",
      "[-425.0912   -63.24414]\n",
      "[-79.83104 136.1161 ]\n",
      "[ -53.65985 -294.18658]\n",
      "[ 188.05983 -106.03253]\n",
      "[24.02272  -7.850095]\n",
      "[273.05038 344.70337]\n",
      "[207.16702   39.179672]\n",
      "[-248.3637     49.335014]\n",
      "[-123.9823   210.85909]\n",
      "[-333.6178     29.257086]\n",
      "[265.26584 -42.35317]\n",
      "[-292.61975 -185.48045]\n",
      "[-205.11183 -175.99088]\n",
      "[-254.25801 -373.70514]\n",
      "[441.21143    -4.3697877]\n",
      "[ -27.370829 -453.50128 ]\n",
      "[ 64.668724 242.25552 ]\n",
      "[-22.223679 -54.502094]\n",
      "[165.7487  348.99625]\n",
      "[  24.045874 -295.86343 ]\n",
      "[ 67.542435 -85.52236 ]\n",
      "[158.57298  -29.359833]\n",
      "[-169.2064   167.38293]\n",
      "[ 13.493331 383.5443  ]\n",
      "[212.96393 380.05966]\n",
      "[-61.77767 157.9465 ]\n",
      "[ 317.22256  -109.599724]\n",
      "[173.91777  -15.425483]\n",
      "[-323.36057   -53.819683]\n",
      "[-164.78294 -172.47075]\n",
      "[-135.9435    -44.030193]\n",
      "[-251.11455  130.3915 ]\n",
      "[-203.01126    25.850262]\n",
      "[-68.91417   51.038258]\n",
      "[25.627926 83.36262 ]\n",
      "[-159.02373 -346.80826]\n",
      "[-109.94755  -37.35127]\n",
      "[214.30634 129.27124]\n",
      "[ 58.438335 361.1978  ]\n",
      "[127.79851 414.29218]\n",
      "[399.0264  -55.47634]\n",
      "[-370.78598  -23.87224]\n",
      "[-45.735195 104.699554]\n",
      "[291.17102 -79.70761]\n",
      "[ 30.384064 124.89884 ]\n",
      "[ 249.20552 -291.7584 ]\n",
      "[-214.23222     -2.8586452]\n",
      "[  65.35204 -197.64626]\n",
      "[ 98.37476 -69.07776]\n",
      "[ -34.636917 -253.88988 ]\n",
      "[210.84767     -0.35336635]\n",
      "[  27.289007 -276.20767 ]\n",
      "[215.99733 -84.71047]\n",
      "[185.5331     15.3733425]\n",
      "[-130.06021  104.23603]\n",
      "[65.863655  -2.5413663]\n",
      "[-141.28593   -80.931694]\n",
      "[-84.50691 -35.02876]\n",
      "[ -86.53175 -237.37779]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x1152 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\"Creates and TSNE model and plots it\"\n",
    "labels = []\n",
    "tokens = []\n",
    "\n",
    "    \n",
    "tsne_model = TSNE(perplexity=40, n_components=2, init='pca', n_iter=2500, random_state=23)\n",
    "new_values = tsne_model.fit_transform(vectors)\n",
    "\n",
    "x = []\n",
    "y = []\n",
    "for value in new_values:\n",
    "    print(value)\n",
    "    x.append(value[0])\n",
    "    y.append(value[1])\n",
    "        \n",
    "plt.figure(figsize=(16, 16)) \n",
    "for i in range(len(x)):\n",
    "    plt.scatter(x[i],y[i],marker='o',c='blue')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
